diff --git a/README.md b/README.md
index 9a48115a2..cfaf8d587 100644
--- a/README.md
+++ b/README.md
@@ -34,7 +34,7 @@ Key features:
    with an interface similar in feel and style to the widely
    used [pandas.DataFrame](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html)
  - Advanced visualization and plotting functions
-   (see the [gallery](https://pyam-iamc.readthedocs.io/en/stable/examples/index.html))
+   (see the [gallery](https://pyam-iamc.readthedocs.io/en/stable/gallery/index.html))
  - Diagnostic checks for scripted validation of scenario data and results
 
 Data model
diff --git a/RELEASE_NOTES.md b/RELEASE_NOTES.md
index 8e8c1e03a..584ecf5c7 100644
--- a/RELEASE_NOTES.md
+++ b/RELEASE_NOTES.md
@@ -2,17 +2,21 @@
 
 ## API changes
 
-Several PRs in this release changed the name of plotting functions
-for consistency with matplotlib and seaborn. 
+Several PRs in this release changed the implementation of the plotting library 
+for better UX and consistency with **pandas**, **matplotlib** and **seaborn**. 
 
- - `stackplot()` for `stack_plot()`
- - `barplot()` for `bar_plot()`
+Replace the calls to plotting features by the following:
+ - `plot(...)` (or `plot(kind='line', ...)`) for `line_plot()`
+ - `plot.stack(...)` for `stack_plot()`
+ - `plot.bar()` for `bar_plot()`
+ - ...
 
-These PR also adds an `order` arg to the plotting functions, and the levels
+These PRs also add an `order` arg to the plotting functions, and the levels
 are ordered based on the `run_control()['order']` dictionary by default.
 
 ## Individual updates
 
+- [#473](https://github.com/IAMconsortium/pyam/pull/473) Refactor to plotting API following pandas/matplotlib implementation
 - [#472](https://github.com/IAMconsortium/pyam/pull/472) Add a ´sankey()` example to the plotting gallery
 - [#470](https://github.com/IAMconsortium/pyam/pull/470) Add two types of `order` arg to `barplot()`
 - [#467](https://github.com/IAMconsortium/pyam/pull/467) Refactor the GAMS-pyam tutorial to use the gamstransfer module
diff --git a/doc/source/.gitignore b/doc/source/.gitignore
index fb0ea69ad..9ffffd16b 100644
--- a/doc/source/.gitignore
+++ b/doc/source/.gitignore
@@ -1,4 +1,5 @@
-examples
+# exclude built gallery folder (built by sphinx-gallery module)
+gallery
 modules
 #*
 .#*
diff --git a/doc/source/api.rst b/doc/source/api.rst
index 8678795b8..f77d17cfd 100644
--- a/doc/source/api.rst
+++ b/doc/source/api.rst
@@ -1,6 +1,6 @@
 .. currentmodule:: pyam
 
-API reference
+API Reference
 =============
 
 This page gives an overview of the public |pyam| features, objects, functions
diff --git a/doc/source/api/plotting.rst b/doc/source/api/plotting.rst
index 41b958692..a119d6061 100644
--- a/doc/source/api/plotting.rst
+++ b/doc/source/api/plotting.rst
@@ -3,6 +3,39 @@
 Plotting library
 ================
 
+The plotting API(s)
+-------------------
+
+There are three ways to use the |pyam| plotting library.
+
+1. Using the plot feature as an attribute of the :class:`IamDataFrame`:
+
+   .. code-block:: python
+
+      IamDataFrame.plot.<kind>(**kwargs)
+
+2. Using the plot feature as a function with a `kind` keyword argument:
+
+   .. code-block:: python
+
+      IamDataFrame.plot(kind='<kind>', **kwargs)
+
+   This function defaults to the :meth:`pyam.plotting.line` type.
+
+3. Calling any function of either the :mod:`plotting`
+   or the :mod:`figures` module directly via
+
+   .. code-block:: python
+
+      pyam.<module>.<kind>(df, **kwargs)
+
+   where `df` is either an :class:`IamDataFrame`
+   or a suitable :class:`pandas.DataFrame`.
+
+Check out the `Plotting Gallery`_ for examples!
+
+.. _`Plotting Gallery` : ../gallery/index.html
+
 The RunControl configuration
 ----------------------------
 
@@ -27,7 +60,7 @@ or as the path to a yaml file with a similar structure:
 
     pyam.run_control().update(<file.yaml>)
 
-See `this example`_ from the AR6 WG1 work using |pyam| plotting.
+See `this example`_ from the AR6 WG1 using |pyam| plotting via a `yaml` file.
 
 .. _`this example`: https://github.com/gidden/ar6-wg1-ch6-emissions/blob/master/plotting.yaml
 
@@ -37,6 +70,16 @@ to the RunControl.
 Plotting functions
 ------------------
 
-.. autofunction:: pyam.plotting.stackplot
+.. autofunction:: pyam.plotting.line
+
+.. autofunction:: pyam.plotting.stack
+
+.. autofunction:: pyam.plotting.bar
+
+.. autofunction:: pyam.plotting.box
+
+.. autofunction:: pyam.plotting.scatter
+
+.. autofunction:: pyam.plotting.pie
 
 .. autofunction:: pyam.figures.sankey
diff --git a/doc/source/conf.py b/doc/source/conf.py
index 022f8ef8f..9a4661cc5 100644
--- a/doc/source/conf.py
+++ b/doc/source/conf.py
@@ -320,6 +320,7 @@
     'pint': ('https://pint.readthedocs.io/en/stable', None),
     'ixmp': ('https://docs.messageix.org/projects/ixmp/en/stable/', None),
     'matplotlib': ('https://matplotlib.org', None),
+    'plotly': ('https://plotly.com/python-api-reference/', None),
     'pandas_datareader':
         ('https://pandas-datareader.readthedocs.io/en/stable', None)
 }
@@ -329,19 +330,11 @@
 
 sphinx_gallery_conf = {
     'doc_module': ('plotly',),
-    # path to your examples scripts
-    'examples_dirs': 'examples_source',
+    # path to your example scripts
+    'examples_dirs': 'examples',
     # path where to save gallery generated examples
-    'gallery_dirs': 'examples',
-    'subsection_order':
-        ExplicitOrder(['../examples/plot_timeseries',
-                       '../examples/plot_ranges',
-                       '../examples/plot_stack',
-                       '../examples/plot_bar',
-                       '../examples/plot_boxplot',
-                       '../examples/plot_pie',
-                       '../examples/plot_sankey']),
-    'reference_url': {'plotly': None,},
+    'gallery_dirs': 'gallery',
+    'reference_url': {'plotly': None, 'matplotlib': None, 'pyam': None},
     'image_scrapers': image_scrapers,
 }
 
diff --git a/doc/source/examples_source/README.txt b/doc/source/examples/README.txt
similarity index 100%
rename from doc/source/examples_source/README.txt
rename to doc/source/examples/README.txt
diff --git a/doc/source/examples_source/plot_bar.py b/doc/source/examples/plot_bar.py
similarity index 86%
rename from doc/source/examples_source/plot_bar.py
rename to doc/source/examples/plot_bar.py
index 55c139342..3ec3742ee 100644
--- a/doc/source/examples_source/plot_bar.py
+++ b/doc/source/examples/plot_bar.py
@@ -35,7 +35,7 @@
 args = dict(model='WITCH-GLOBIOM 4.4', scenario='CD-LINKS_NPi2020_1000')
 data = df.filter(**args, variable='Primary Energy|*', region='World')
 
-data.barplot(stacked=True, title='Primary energy mix')
+data.plot.bar(stacked=True, title='Primary energy mix')
 plt.legend(loc=1)
 plt.tight_layout()
 plt.show()
@@ -46,7 +46,7 @@
 #
 # We can flip that round for a horizontal chart.
 
-data.barplot(stacked=True, orient='h', title='Primary energy mix')
+data.plot.bar(stacked=True, orient='h', title='Primary energy mix')
 plt.legend(loc=1)
 plt.tight_layout()
 plt.show()
@@ -64,8 +64,8 @@
     .filter(region='World', keep=False)
 )
 
-data.barplot(bars='region', stacked=True,
-             title='CO2 emissions by region', cmap='tab20')
+data.plot.bar(bars='region', stacked=True,
+              title='CO2 emissions by region', cmap='tab20')
 plt.legend(loc=1)
 plt.tight_layout()
 plt.show()
@@ -80,8 +80,8 @@
 from pyam.plotting import add_net_values_to_barplot
 
 fig, ax = plt.subplots()
-data.barplot(ax=ax, bars='region', stacked=True,
-             title='CO2 emissions by region', cmap='tab20')
+data.plot.bar(ax=ax, bars='region', stacked=True,
+              title='CO2 emissions by region', cmap='tab20')
 add_net_values_to_barplot(ax)
 plt.legend(loc=1)
 plt.tight_layout()
diff --git a/doc/source/examples_source/plot_boxplot.py b/doc/source/examples/plot_boxplot.py
similarity index 95%
rename from doc/source/examples_source/plot_boxplot.py
rename to doc/source/examples/plot_boxplot.py
index 2ab636416..c8829659e 100644
--- a/doc/source/examples_source/plot_boxplot.py
+++ b/doc/source/examples/plot_boxplot.py
@@ -33,7 +33,7 @@
 data = df.filter(scenario='CD-LINKS_NPi2020_1000',
                  variable='Emissions|CO2', region='World')
 
-data.boxplot(x='year')
+data.plot.box(x='year')
 plt.tight_layout()
 plt.show()
 
@@ -49,7 +49,7 @@
     .filter(region='World', keep=False)
 )
 
-data.boxplot(x='year', by='region', legend=True)
+data.plot.box(x='year', by='region', legend=True)
 
 # We can use matplotlib arguments to make the figure more appealing.
 plt.legend(loc=1)
diff --git a/doc/source/examples_source/plot_pie.py b/doc/source/examples/plot_pie.py
similarity index 94%
rename from doc/source/examples_source/plot_pie.py
rename to doc/source/examples/plot_pie.py
index fbd7957ea..00584b48b 100644
--- a/doc/source/examples_source/plot_pie.py
+++ b/doc/source/examples/plot_pie.py
@@ -34,7 +34,7 @@
                  variable='Primary Energy|*', year=2050,
                  region='World')
 
-data.pie_plot()
+data.plot.pie()
 plt.tight_layout()
 plt.show()
 
@@ -44,7 +44,7 @@
 #
 # Sometimes a legend is preferable to labels, so we can use that instead.
 
-data.pie_plot(labels=None, legend=True)
+data.plot.pie(labels=None, legend=True)
 plt.tight_layout()
 plt.show()
 
@@ -61,6 +61,6 @@
               variable='Emissions|CO2', year=2050)
     .filter(region='World', keep=False)
 )
-data.pie_plot(category='region', cmap='tab20')
+data.plot.pie(category='region', cmap='tab20')
 plt.tight_layout()
 plt.show()
diff --git a/doc/source/examples_source/plot_ranges.py b/doc/source/examples/plot_ranges.py
similarity index 89%
rename from doc/source/examples_source/plot_ranges.py
rename to doc/source/examples/plot_ranges.py
index 7deead5b3..ffde6e5ec 100644
--- a/doc/source/examples_source/plot_ranges.py
+++ b/doc/source/examples/plot_ranges.py
@@ -33,7 +33,7 @@
 data = df.filter(scenario='CD-LINKS*',
                  variable='Emissions|CO2', region='World')
 
-data.line_plot(color='scenario', fill_between=True)
+data.plot(color='scenario', fill_between=True)
 plt.tight_layout()
 plt.show()
 
@@ -45,7 +45,7 @@
 # or it can be provided specific arguments as a dictionary:
 # in this illustration, we choose a very low transparency value.
 
-data.line_plot(color='scenario', fill_between=dict(alpha=0.15))
+data.plot(color='scenario', fill_between=dict(alpha=0.15))
 plt.tight_layout()
 plt.show()
 
@@ -57,7 +57,6 @@
 # range of data in the final time period using `final_ranges`. Similar to
 # `fill_between` it can either be true or have specific arguments.
 
-data.line_plot(color='scenario', fill_between=True,
-               final_ranges=dict(linewidth=5))
+data.plot(color='scenario', fill_between=True, final_ranges=dict(linewidth=5))
 plt.tight_layout()
 plt.show()
diff --git a/doc/source/examples_source/plot_sankey.py b/doc/source/examples/plot_sankey.py
similarity index 97%
rename from doc/source/examples_source/plot_sankey.py
rename to doc/source/examples/plot_sankey.py
index 31f9fa4bc..f7ad843a9 100644
--- a/doc/source/examples_source/plot_sankey.py
+++ b/doc/source/examples/plot_sankey.py
@@ -70,6 +70,6 @@
         ('Gas Network & Power Generation', 'Gas Demand'),
 }
 
-fig = df.filter(year=2050).sankey(mapping=sankey_mapping)
+fig = df.filter(year=2050).plot.sankey(mapping=sankey_mapping)
 # calling `show()` is necessary to have the thumbnail in the gallery overview
 plotly.io.show(fig)
diff --git a/doc/source/examples_source/plot_stack.py b/doc/source/examples/plot_stack.py
similarity index 92%
rename from doc/source/examples_source/plot_stack.py
rename to doc/source/examples/plot_stack.py
index 7738df971..f63124284 100644
--- a/doc/source/examples_source/plot_stack.py
+++ b/doc/source/examples/plot_stack.py
@@ -32,7 +32,7 @@
 data = df.filter(model=model, scenario=scenario,
                  variable='Primary Energy|*', region='World')
 
-data.stackplot(title=scenario)
+data.plot.stack(title=scenario)
 plt.legend(loc=1)
 plt.tight_layout()
 plt.show()
@@ -47,8 +47,8 @@
     .filter(region='World', keep=False)
 )
 
-data.stackplot(stack='region', cmap='tab20',
-               title=scenario, total=True)
+data.plot.stack(stack='region', cmap='tab20',
+                title=scenario, total=True)
 plt.legend(loc=1)
 plt.tight_layout()
 plt.show()
diff --git a/doc/source/examples_source/plot_timeseries.py b/doc/source/examples/plot_timeseries.py
similarity index 94%
rename from doc/source/examples_source/plot_timeseries.py
rename to doc/source/examples/plot_timeseries.py
index e40815d43..936fe697e 100644
--- a/doc/source/examples_source/plot_timeseries.py
+++ b/doc/source/examples/plot_timeseries.py
@@ -36,5 +36,5 @@
     .filter(region='World', keep=False)
 )
 
-data.line_plot(color='region', title='CO2 emissions by region')
+data.plot(color='region', title='CO2 emissions by region')
 data.timeseries()
diff --git a/doc/source/examples_source/sankey_data.csv b/doc/source/examples/sankey_data.csv
similarity index 100%
rename from doc/source/examples_source/sankey_data.csv
rename to doc/source/examples/sankey_data.csv
diff --git a/doc/source/examples_source/tutorial_data.csv b/doc/source/examples/tutorial_data.csv
similarity index 100%
rename from doc/source/examples_source/tutorial_data.csv
rename to doc/source/examples/tutorial_data.csv
diff --git a/doc/source/index.rst b/doc/source/index.rst
index d5f3d7c9e..f729659da 100644
--- a/doc/source/index.rst
+++ b/doc/source/index.rst
@@ -65,7 +65,7 @@ The source code for |pyam| is available on `Github`_.
    data.html
 
 .. _`gallery`:
-   examples/index.html
+   gallery/index.html
 
 .. _`Github`:
    https://github.com/IAMconsortium/pyam
@@ -81,7 +81,7 @@ Table of Contents
    contributing
    data
    tutorials
-   examples/index
+   gallery/index
    api
 
 Copyright & License
diff --git a/doc/source/tutorials/GAMS_to_pyam.ipynb b/doc/source/tutorials/GAMS_to_pyam.ipynb
index 98c783bea..d795dc8ad 100644
--- a/doc/source/tutorials/GAMS_to_pyam.ipynb
+++ b/doc/source/tutorials/GAMS_to_pyam.ipynb
@@ -914,14 +914,14 @@
     }
    ],
    "source": [
-    "df.filter(variable='supply|*').bar_plot(x='region')"
+    "df.filter(variable='supply|*').plot.bar(x='region')"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Visit the **pyam** [plotting gallery](https://pyam-iamc.readthedocs.io/en/stable/examples/index.html)\n",
+    "Visit the **pyam** [plotting gallery](https://pyam-iamc.readthedocs.io/en/stable/gallery/index.html)\n",
     "for more features and options!"
    ]
   },
diff --git a/doc/source/tutorials/aggregating_variables_and_plotting_with_negative_values.ipynb b/doc/source/tutorials/aggregating_variables_and_plotting_with_negative_values.ipynb
index f3c8724c9..0372709e6 100644
--- a/doc/source/tutorials/aggregating_variables_and_plotting_with_negative_values.ipynb
+++ b/doc/source/tutorials/aggregating_variables_and_plotting_with_negative_values.ipynb
@@ -64,7 +64,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Pyam's `stack_plot` method plots the stacks in the clearest way possible, even when some emissions are negative. The optional `total` keyword arguments also allows the user to include a total line on their plot."
+    "Pyam's `stackplot` method plots the stacks in the clearest way possible, even when some emissions are negative. The optional `total` keyword arguments also allows the user to include a total line on their plot."
    ]
   },
   {
@@ -73,7 +73,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.stack_plot();"
+    "df.plot.stack();"
    ]
   },
   {
@@ -82,7 +82,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.stack_plot(total=True);"
+    "df.plot.stack(total=True);"
    ]
   },
   {
@@ -98,7 +98,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.stack_plot(alpha=0.5, total={\"color\": \"grey\", \"ls\": \"--\", \"lw\": 2.0});"
+    "df.plot.stack(alpha=0.5, total={\"color\": \"grey\", \"ls\": \"--\", \"lw\": 2.0});"
    ]
   },
   {
@@ -114,7 +114,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.filter(variable=\"Emissions|CO2|Energy*\").stack_plot(total=True);"
+    "df.filter(variable=\"Emissions|CO2|Energy*\").plot.stack(total=True);"
    ]
   },
   {
@@ -132,7 +132,7 @@
    "source": [
     "pdf = df.copy()\n",
     "afoluluc_vars = [\"Emissions|CO2|LUC\", \"Emissions|CO2|Agg\"]\n",
-    "fossil_vars = list(set(pdf.variables()) - set(afoluluc_vars))\n",
+    "fossil_vars = list(set(pdf.variable) - set(afoluluc_vars))\n",
     "pdf.aggregate(\n",
     "    \"Emissions|CO2|AFOLULUC\", \n",
     "    components=afoluluc_vars, \n",
@@ -146,7 +146,7 @@
     "pdf.filter(variable=[\n",
     "    \"Emissions|CO2|AFOLULUC\",\n",
     "    \"Emissions|CO2|Fossil\"\n",
-    "]).stack_plot(total=True);"
+    "]).plot.stack(total=True);"
    ]
   },
   {
@@ -227,8 +227,8 @@
     "    variable=\"Emissions|CO2|AFOLU\"\n",
     ").filter(\n",
     "    region=\"World\", keep=False\n",
-    ").stack_plot(stack=\"region\", ax=ax)\n",
-    "df.filter(variable=\"Emissions|CO2|AFOLU\", region=\"World\").line_plot(ax=ax, color=\"black\");"
+    ").plot.stack(stack=\"region\", ax=ax)\n",
+    "df.filter(variable=\"Emissions|CO2|AFOLU\", region=\"World\").plot(ax=ax, color=\"black\");"
    ]
   },
   {
@@ -274,8 +274,8 @@
     "    variable=\"Emissions|CO2|Fossil\"\n",
     ").filter(\n",
     "    region=\"World\", keep=False\n",
-    ").stack_plot(stack=\"region\", ax=ax)\n",
-    "df.filter(variable=\"Emissions|CO2|Fossil\", region=\"World\").line_plot(ax=ax, color=\"black\");"
+    ").plot.stack(stack=\"region\", ax=ax)\n",
+    "df.filter(variable=\"Emissions|CO2|Fossil\", region=\"World\").plot(ax=ax, color=\"black\");"
    ]
   },
   {
diff --git a/doc/source/tutorials/iiasa_dbs.ipynb b/doc/source/tutorials/iiasa_dbs.ipynb
index bb31d6710..b4389f3ab 100644
--- a/doc/source/tutorials/iiasa_dbs.ipynb
+++ b/doc/source/tutorials/iiasa_dbs.ipynb
@@ -118,7 +118,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ax = df.filter(variable='Emissions|CO2').line_plot(\n",
+    "ax = df.filter(variable='Emissions|CO2').plot(\n",
     "    color='category', \n",
     "    legend=dict(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
     ")"
@@ -262,7 +262,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ax = df.filter(variable='Primary Energy|Coal').line_plot(\n",
+    "ax = df.filter(variable='Primary Energy|Coal').plot(\n",
     "    color='scenario', \n",
     "    legend=dict(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
     ")"
diff --git a/doc/source/tutorials/legends.ipynb b/doc/source/tutorials/legends.ipynb
index 9568c626f..3e9ebbcf5 100644
--- a/doc/source/tutorials/legends.ipynb
+++ b/doc/source/tutorials/legends.ipynb
@@ -47,7 +47,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.line_plot()"
+    "df.plot()"
    ]
   },
   {
@@ -64,7 +64,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.line_plot(color='model')"
+    "df.plot(color='model')"
    ]
   },
   {
@@ -80,7 +80,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.line_plot(color='model', legend=dict(loc='center left'))"
+    "df.plot(color='model', legend=dict(loc='center left'))"
    ]
   },
   {
@@ -105,7 +105,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.line_plot(color='model', legend=OUTSIDE_LEGEND['right'])"
+    "df.plot(color='model', legend=OUTSIDE_LEGEND['right'])"
    ]
   },
   {
@@ -114,7 +114,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.line_plot(color='model', legend=OUTSIDE_LEGEND['bottom'])"
+    "df.plot(color='model', legend=OUTSIDE_LEGEND['bottom'])"
    ]
   }
  ],
diff --git a/doc/source/tutorials/pyam_first_steps.ipynb b/doc/source/tutorials/pyam_first_steps.ipynb
index 2844f7a3c..dacbfd0d2 100644
--- a/doc/source/tutorials/pyam_first_steps.ipynb
+++ b/doc/source/tutorials/pyam_first_steps.ipynb
@@ -429,7 +429,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.filter(variable='Emissions|CO2', region='World').line_plot()"
+    "df.filter(variable='Emissions|CO2', region='World').plot()"
    ]
   },
   {
@@ -446,14 +446,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.filter(variable='Emissions|CO2', region='World').line_plot(color='scenario')"
+    "df.filter(variable='Emissions|CO2', region='World').plot(color='scenario')"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The section on categorization will show more options of the plotting features, as well as a method to set specific colors for different categories. For more information, look at the other tutorials and the [plotting gallery](https://pyam-iamc.readthedocs.io/en/stable/examples/index.html)."
+    "The section on categorization will show more options of the plotting features, as well as a method to set specific colors for different categories. For more information, look at the other tutorials and the [plotting gallery](https://pyam-iamc.readthedocs.io/en/stable/gallery/index.html)."
    ]
   },
   {
@@ -571,7 +571,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_world.filter(variable='Emissions|CO2').line_plot()"
+    "df_world.filter(variable='Emissions|CO2').plot()"
    ]
   },
   {
@@ -618,8 +618,8 @@
     "\n",
     "df_world_co2 = df_world.filter(variable='Emissions|CO2')\n",
     "\n",
-    "df_world_co2.line_plot(ax=ax[0])\n",
-    "df_world_co2.filter(exclude=False).line_plot(ax=ax[1])"
+    "df_world_co2.plot(ax=ax[0])\n",
+    "df_world_co2.filter(exclude=False).plot(ax=ax[1])"
    ]
   },
   {
@@ -676,7 +676,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df.filter(variable='Temperature').line_plot()"
+    "df.filter(variable='Temperature').plot()"
    ]
   },
   {
diff --git a/pyam/core.py b/pyam/core.py
index 0bc82ed75..aa3a0927f 100755
--- a/pyam/core.py
+++ b/pyam/core.py
@@ -25,7 +25,6 @@
 except (ImportError, AttributeError):
     has_ix = False
 
-from pyam import figures
 from pyam import plotting
 from pyam.run_control import run_control
 from pyam.utils import (
@@ -54,7 +53,7 @@
 )
 from pyam.read_ixmp import read_ix
 from pyam.timeseries import fill_series
-from pyam.plotting import mpl_args_to_meta_cols
+from pyam.plotting import PlotAccessor, mpl_args_to_meta_cols
 from pyam._aggregate import _aggregate, _aggregate_region, _aggregate_time,\
     _aggregate_recursive, _group_and_agg
 from pyam.units import convert_unit
@@ -184,6 +183,9 @@ def _init(self, data, meta=None, **kwargs):
         if 'exec' in run_control():
             self._execute_run_control()
 
+        # add the `plot` handler
+        self.plot = PlotAccessor(self)
+
     def __getitem__(self, key):
         _key_check = [key] if isstr(key) else key
         if set(_key_check).issubset(self.meta.columns):
@@ -1725,11 +1727,14 @@ def load_meta(self, path, *args, **kwargs):
         # set column `exclude` to bool
         self.meta.exclude = self.meta.exclude.astype('bool')
 
-    def line_plot(self, x='year', y='value', **kwargs):
-        """Plot timeseries lines of existing data
+    def line_plot(self, *args, **kwargs):
+        """Deprecated, please use `IamDataFrame.plot()`"""
+        deprecation_warning('Please use `IamDataFrame.plot()`.')
+        return self.plot(*args, **kwargs)
 
-        see pyam.plotting.line_plot() for all available options
-        """
+    def _line_plot(self, x='year', y='value', **kwargs):
+        """Plot timeseries lines of existing data"""
+        # TODO merge with `plot.line` and deprecate
         df = self.as_pandas(meta_cols=mpl_args_to_meta_cols(self, **kwargs))
 
         # pivot data if asked for explicit variable name
@@ -1750,68 +1755,37 @@ def line_plot(self, x='year', y='value', **kwargs):
             if x != 'year' and y != 'year':
                 df = df.drop('year', axis=1)  # years causes nan's
 
-        ax, handles, labels = plotting.line_plot(
-            df.dropna(), x=x, y=y, **kwargs)
+        ax, handles, labels = plotting.line(df.dropna(), x=x, y=y, **kwargs)
         return ax
 
-    def stackplot(self, *args, **kwargs):
-        """Plot a stacked area chart of timeseries data
-
-        See `pyam.plotting.stackplot <plotting.html#pyam.plotting.stackplot>`_
-        for details.
-        """
-        return plotting.stackplot(self, *args, **kwargs)
-
     def stack_plot(self, *args, **kwargs):
-        """Deprecated, please use `IamDataFrame.stackplot()`"""
-        deprecation_warning('Please use `stackplot()`.')
-        return self.stackplot(*args, **kwargs)
-
-    def barplot(self, *args, **kwargs):
-        """Plot a grouped or stacked bar chart
-
-        See `pyam.plotting.barplot <plotting.html#pyam.plotting.barplot>`_
-        for details.
-        """
-        return plotting.barplot(self, *args, **kwargs)
+        """Deprecated, please use `IamDataFrame.plot.stack()`"""
+        deprecation_warning('Please use `IamDataFrame.plot.stack()`.')
+        return self.plot.stack(*args, **kwargs)
 
     def bar_plot(self, *args, **kwargs):
-        """Deprecated, please use `IamDataFrame.barplot()`"""
-        deprecation_warning('Please use `barplot()`.')
-        return self.barplot(*args, **kwargs)
+        """Deprecated, please use `IamDataFrame.plot.bar()`"""
+        deprecation_warning('Please use `plot.bar()`.')
+        return self.plot.bar(*args, **kwargs)
 
     def boxplot(self, *args, **kwargs):
-        """Plot boxplot of existing data
-
-        see pyam.plotting.boxplot() for all available options
-        """
-        df = self.as_pandas()
-        ax = plotting.boxplot(df, *args, **kwargs)
-        return ax
+        """Deprecated, please use `IamDataFrame.plot.box()`"""
+        deprecation_warning('Please use `IamDataFrame.plot.box()`.')
+        return self.plot.box(**kwargs)
 
     def pie_plot(self, *args, **kwargs):
-        """Plot a pie chart
-
-        see pyam.plotting.pie_plot() for all available options
-        """
-        # TODO: select only relevant meta columns
-        df = self.as_pandas()
-        ax = plotting.pie_plot(df, *args, **kwargs)
-        return ax
-
-    def sankey(self, mapping):
-        """Plot a sankey diagram
-
-        See `pyam.figures.sankey <plotting.html#pyam.plotting.stackplot>`_
-        for details.
-        """
-        return figures.sankey(self, mapping)
-
-    def scatter(self, x, y, **kwargs):
-        """Plot a scatter chart using meta indicators as columns
-
-        see pyam.plotting.scatter() for all available options
-        """
+        """Deprecated, please use `IamDataFrame.plot.pie()`"""
+        deprecation_warning('Please use `IamDataFrame.plot.pie()`.')
+        return self.plot.pie(*args, **kwargs)
+
+    def scatter(self, *args, **kwargs):
+        """Deprecated, please use `IamDataFrame.plot.scatter()`"""
+        deprecation_warning('Please use `IamDataFrame.plot.scatter()`.')
+        return self.plot.scatter(*args, **kwargs)
+
+    def _scatter(self, x, y, **kwargs):
+        """Plot a scatter chart using meta indicators as columns"""
+        # TODO merge with `plot.scatter` and deprecate
         variables = self.data['variable'].unique()
         xisvar = x in variables
         yisvar = y in variables
diff --git a/pyam/figures.py b/pyam/figures.py
index a0aea877d..455dde24a 100755
--- a/pyam/figures.py
+++ b/pyam/figures.py
@@ -27,7 +27,7 @@ def sankey(df, mapping):
 
         Returns
         -------
-        fig : plotly.graph_objs._figure.Figure
+        fig : :class:`plotly.graph_objects.Figure`
     """
     # Check for duplicates
     for col in [name for name in df._data.index.names if name != 'variable']:
diff --git a/pyam/plotting.py b/pyam/plotting.py
index 97f6e882d..9906cdca1 100644
--- a/pyam/plotting.py
+++ b/pyam/plotting.py
@@ -12,10 +12,12 @@
 
 from pyam.logging import deprecation_warning
 from pyam.run_control import run_control
+from pyam import figures
 from pyam.timeseries import cross_threshold
 from pyam.utils import META_IDX, IAMC_IDX, SORT_IDX, isstr, islistable,\
     _raise_data_error
 
+
 # TODO: this is a hotfix for changes in pandas 0.25.0, per discussions on the
 # pandas-dev listserv, we should try to ask if matplotlib would make it a
 # standard feature in their library
@@ -70,6 +72,39 @@
 }
 
 
+class PlotAccessor():
+    """Make plots of IamDataFrame instances"""
+    def __init__(self, df):
+        self._parent = df
+
+    def __call__(self, kind='line', *args, **kwargs):
+        return getattr(self, kind)(**kwargs)
+
+    def line(self, **kwargs):
+        self._parent._line_plot(**kwargs)
+
+    def bar(self, **kwargs):
+        return bar(self._parent, **kwargs)
+
+    def stack(self, **kwargs):
+        return stack(self._parent, **kwargs)
+
+    def hist(self, **kwargs):
+        raise NotImplementedError('Histogram plot not implemented yet!')
+
+    def box(self, **kwargs):
+        return box(self._parent, **kwargs)
+
+    def pie(self, **kwargs):
+        return pie(self._parent, **kwargs)
+
+    def scatter(self, *args, **kwargs):
+        return self._parent._scatter(*args, **kwargs)
+
+    def sankey(self, *args, **kwargs):
+        return figures.sankey(self._parent, *args, **kwargs)
+
+
 def reset_default_props(**kwargs):
     """Reset properties to initial cycle point"""
     global _DEFAULT_PROPS
@@ -210,31 +245,41 @@ def reshape_mpl(df, x, y, idx_cols, **kwargs):
     return df
 
 
-def pie_plot(df, value='value', category='variable',
-             ax=None, legend=False, title=True, cmap=None,
-             **kwargs):
-    """Plot data as a bar chart.
+def pie(df, value='value', category='variable', legend=False, title=True,
+        ax=None, cmap=None, **kwargs):
+    """Plot data as a pie chart.
 
     Parameters
     ----------
-    df : pd.DataFrame
-        Data to plot as a long-form data frame
+    df : :class:`pyam.IamDataFrame`, :class:`pandas.DataFrame`
+        Data to be plotted
     value : string, optional
         The column to use for data values
     category : string, optional
         The column to use for labels
-    ax : matplotlib.Axes, optional
     legend : bool, optional
-        Include a legend
+        Include a legend.
     title : bool or string, optional
         Display a default or custom title.
+    ax : :class:`matplotlib.axes.Axes`, optional
     cmap : string, optional
-        A colormap to use.
-    kwargs : Additional arguments to pass to the pd.DataFrame.plot() function
+        The name of a registered colormap.
+    kwargs
+        Additional arguments passed to :meth:`pandas.DataFrame.plot`.
+
+    Returns
+    -------
+    ax : :class:`matplotlib.axes.Axes`
+        Modified `ax` or new instance
     """
+    # cast to DataFrame if necessary
+    # TODO: select only relevant meta columns
+    if not isinstance(df, pd.DataFrame):
+        df = df.as_pandas()
+
     for col in set(SORT_IDX) - set([category]):
         if len(df[col].unique()) > 1:
-            msg = 'Can not plot multiple {}s in pie_plot with value={},' +\
+            msg = 'Can not plot multiple {}s in a pie plot with value={},' +\
                 ' category={}'
             raise ValueError(msg.format(col, value, category))
 
@@ -273,10 +318,9 @@ def pie_plot(df, value='value', category='variable',
     return ax
 
 
-def stackplot(df, x='year', y='value', stack='variable', order=None,
-              ax=None, legend=True, title=True, cmap=None, total=None,
-              **kwargs):
-    """Plot stacked area chart of timeseries data
+def stack(df, x='year', y='value', stack='variable', order=None, total=None,
+          legend=True, title=True, ax=None, cmap=None, **kwargs):
+    """Plot a stacked area chart of timeseries data
 
     Parameters
     ----------
@@ -292,20 +336,25 @@ def stackplot(df, x='year', y='value', stack='variable', order=None,
          The order to plot the stack levels and the legend. If not specified,
          order by :meth:`run_control()['order'][\<stack\>] <pyam.run_control>`
          (where available) or alphabetical.
-    ax : matplotlib.Axes, optional
-    legend : bool, optional
-        Include a legend
-    title : bool or string, optional
-        Display a default or custom title.
-    cmap : string, optional
-        A colormap to use.
     total : bool or dict, optional
         If True, plot a total line with default |pyam| settings. If a dict,
         then plot the total line using the dict key-value pairs as keyword
         arguments to :meth:`matplotlib.axes.Axes.plot`.
         If None, do not plot the total line.
+    legend : bool, optional
+        Include a legend.
+    title : bool or string, optional
+        Display a default or custom title.
+    ax : :class:`matplotlib.axes.Axes`, optional
+    cmap : string, optional
+        The name of a registered colormap.
     kwargs
-        Additional arguments to pass to :meth:`pandas.DataFrame.plot`
+        Additional arguments passed to :meth:`pandas.DataFrame.plot`
+
+    Returns
+    -------
+    ax : :class:`matplotlib.axes.Axes`
+        Modified `ax` or new instance
     """
     # cast to DataFrame if necessary
     # TODO: select only relevant meta columns
@@ -405,9 +454,8 @@ def as_series(index, name):
     return ax
 
 
-def barplot(df, x='year', y='value', bars='variable', order=None,
-            bars_order=None, ax=None, orient='v', legend=True, title=True,
-            cmap=None, **kwargs):
+def bar(df, x='year', y='value', bars='variable', order=None, bars_order=None,
+        orient='v', legend=True, title=True, ax=None, cmap=None, **kwargs):
     """Plot data as a stacked or grouped bar chart
 
     Parameters
@@ -425,16 +473,22 @@ def barplot(df, x='year', y='value', bars='variable', order=None,
          If not specified, order
          by :meth:`run_control()['order'][\<stack\>] <pyam.run_control>`
          (where available) or alphabetical.
-    ax : matplotlib.Axes, optional
     orient : string, optional
         Vertical or horizontal orientation.
     legend : bool, optional
-        Include a legend
+        Include a legend.
     title : bool or string, optional
         Display a default or custom title.
+    ax : :class:`matplotlib.axes.Axes`, optional
     cmap : string, optional
-        A colormap to use.
-    kwargs : Additional arguments to pass to the pd.DataFrame.plot() function
+        The name of a registered colormap.
+    kwargs
+        Additional arguments passed to :meth:`pandas.DataFrame.plot`
+
+    Returns
+    -------
+    ax : :class:`matplotlib.axes.Axes`
+        Modified `ax` or new instance
     """
     # cast to DataFrame if necessary
     # TODO: select only relevant meta columns
@@ -443,7 +497,7 @@ def barplot(df, x='year', y='value', bars='variable', order=None,
 
     for col in set(SORT_IDX) - set([x, bars]):
         if len(df[col].unique()) > 1:
-            msg = 'Can not plot multiple {}s in barplot with x={}, bars={}'
+            msg = 'Can not plot multiple {}s in bar plot with x={}, bars={}'
             raise ValueError(msg.format(col, x, bars))
 
     if ax is None:
@@ -463,6 +517,10 @@ def barplot(df, x='year', y='value', bars='variable', order=None,
             c = rc['color'][bars][key]
         color.append(c)
 
+    # change year to str to prevent pandas/matplotlib from auto-ordering (#474)
+    if _df.index.name == 'year':
+        _df.index = map(str, _df.index)
+
     # plot data
     kind = 'bar' if orient.startswith('v') else 'barh'
     _df.plot(kind=kind, color=color, ax=ax, **kwargs)
@@ -497,14 +555,14 @@ def barplot(df, x='year', y='value', bars='variable', order=None,
     return ax
 
 
-def boxplot(df, y='value', x='year', by=None,
-            ax=None, legend=True, title=None, **kwargs):
+def box(df, y='value', x='year', by=None, legend=True, title=None, ax=None,
+        **kwargs):
     """ Plot boxplot of data using seaborn.boxplot
 
     Parameters
     ----------
-    df : pandas.DataFrame
-        Data to plot as a long-form data frame
+    df : :class:`pyam.IamDataFrame`, :class:`pandas.DataFrame`
+        Data to be plotted
     y : string, optional
         The column to use for y-axis values representing the distribution
         within the boxplot
@@ -512,16 +570,27 @@ def boxplot(df, y='value', x='year', by=None,
         The column to use for x-axis points, i.e. the number of boxes the plot
         will have
     by : string, optional
-        The column for grouping y-axis values at each x-axis point, i.e. a 3rd
-        dimension.
-        Data should be categorical, not a contiuous variable
-    ax : matplotlib.Axes, optional
+        The column for grouping y-axis values at each x-axis point,
+        i.e. a 3rd dimension. Data should be categorical, not a contiuous
+        variable.
     legend : bool, optional
-        Include a legend
+        Include a legend.
     title : bool or string, optional
-        Display a default or custom title
-    kwargs : Additional arguments to pass to the pd.DataFrame.plot()
+        Display a default or custom title.
+    ax : :class:`matplotlib.axes.Axes`, optional
+    kwargs
+        Additional arguments passed to :meth:`pandas.DataFrame.plot`.
+
+    Returns
+    -------
+    ax : :class:`matplotlib.axes.Axes`
+        Modified `ax` or new instance
     """
+    # cast to DataFrame if necessary
+    # TODO: select only relevant meta columns
+    if not isinstance(df, pd.DataFrame):
+        df = df.as_pandas()
+
     if by:
         rc = run_control()
         if 'palette' not in kwargs and 'color' in rc and by in rc['color']:
@@ -536,7 +605,7 @@ def boxplot(df, y='value', x='year', by=None,
     if ax is None:
         fig, ax = plt.subplots()
 
-    # plot
+    # Create the plot
     sns.boxplot(x=x, y=y, hue=by, data=df, ax=ax, **kwargs)
 
     # Add legend
@@ -592,9 +661,9 @@ def add_net_values_to_barplot(axs, color='k'):
             ax.add_patch(rect)
 
 
-def scatter(df, x, y, ax=None, legend=None, title=None,
-            color=None, marker='o', linestyle=None, cmap=None,
-            groupby=['model', 'scenario'], with_lines=False, **kwargs):
+def scatter(df, x, y, legend=None, title=None, color=None, marker='o',
+            linestyle=None, groupby=['model', 'scenario'], with_lines=False,
+            ax=None, cmap=None, **kwargs):
     """Plot data as a scatter chart.
 
     Parameters
@@ -605,9 +674,10 @@ def scatter(df, x, y, ax=None, legend=None, title=None,
         column to be plotted on the x-axis
     y : str
         column to be plotted on the y-axis
-    ax : matplotlib.Axes, optional
     legend : bool, optional
-        Include a legend (`None` displays legend only if less than 13 entries)
+        Include a legend. By default, show legend only if less than 13 entries.
+        If a dictionary is provided, it will be used as keyword arguments
+        in creating the legend.
     title : bool or string, optional
         Display a custom title.
     color : string, optional
@@ -620,13 +690,20 @@ def scatter(df, x, y, ax=None, legend=None, title=None,
         A valid matplotlib linestyle or column name. If a column name, common
         values will be provided the same linestyle.
         default: None
-    cmap : string, optional
-        A colormap to use.
     groupby : list-like, optional
         Data grouping for plotting.
     with_lines : bool, optional
         Make the scatter plot with lines connecting common data.
-    kwargs : Additional arguments to pass to the pd.DataFrame.plot() function
+    ax : :class:`matplotlib.axes.Axes`, optional
+    cmap : string, optional
+        The name of a registered colormap.
+    kwargs
+        Additional arguments passed to :meth:`pandas.DataFrame.plot`.
+
+    Returns
+    -------
+    ax : :class:`matplotlib.axes.Axes`
+        Modified `ax` or new instance
     """
     if ax is None:
         fig, ax = plt.subplots()
@@ -671,7 +748,7 @@ def scatter(df, x, y, ax=None, legend=None, title=None,
         labels = sorted(list(set(tuple(legend_data))))
         idxs = [legend_data.index(d) for d in labels]
         handles = [handles[i] for i in idxs]
-    if legend is None and len(labels) < 13 or legend is not False:
+    if legend is not False:
         _add_legend(ax, handles, labels, legend)
 
     # add labels and title
@@ -683,10 +760,10 @@ def scatter(df, x, y, ax=None, legend=None, title=None,
     return ax
 
 
-def line_plot(df, x='year', y='value', ax=None, legend=None, title=True,
-              color=None, marker=None, linestyle=None, cmap=None,
-              fill_between=None, final_ranges=None,
-              rm_legend_label=[], **kwargs):
+def line(df, x='year', y='value', legend=None, title=True,
+         color=None, marker=None, linestyle=None,
+         fill_between=None, final_ranges=None,
+         rm_legend_label=[], ax=None, cmap=None, **kwargs):
     """Plot data as lines with or without markers.
 
     Parameters
@@ -697,10 +774,10 @@ def line_plot(df, x='year', y='value', ax=None, legend=None, title=True,
         The column to use for x-axis values
     y : string, optional
         The column to use for y-axis values
-    ax : matplotlib.Axes, optional
     legend : bool or dictionary, optional
-        Add a legend. If a dictionary is provided, it will be used as keyword
-        arguments in creating the legend.
+        Include a legend. By default, show legend only if less than 13 entries.
+        If a dictionary is provided, it will be used as keyword arguments
+        in creating the legend.
     title : bool or string, optional
         Display a default or custom title.
     color : string, optional
@@ -712,8 +789,6 @@ def line_plot(df, x='year', y='value', ax=None, legend=None, title=True,
     linestyle : string, optional
         A valid matplotlib linestyle or column name. If a column name, common
         values will be provided the same linestyle.
-    cmap : string, optional
-        A colormap to use.
     fill_between : boolean or dict, optional
         Fill lines between minima/maxima of the 'color' argument. This can only
         be used if also providing a 'color' argument. If this is True, then
@@ -727,7 +802,16 @@ def line_plot(df, x='year', y='value', ax=None, legend=None, title=True,
         provided instead of defaults.
     rm_legend_label : string, list, optional
         Remove the color, marker, or linestyle label in the legend.
-    kwargs : Additional arguments to pass to the pd.DataFrame.plot() function
+    ax : :class:`matplotlib.axes.Axes`, optional
+    cmap : string, optional
+        The name of a registered colormap.
+    kwargs
+        Additional arguments passed to :meth:`pandas.DataFrame.plot`.
+
+    Returns
+    -------
+    ax : :class:`matplotlib.axes.Axes`
+        Modified `ax` or new instance
     """
     if ax is None:
         fig, ax = plt.subplots()
diff --git a/pyam/utils.py b/pyam/utils.py
index d4728e121..108dc3b13 100644
--- a/pyam/utils.py
+++ b/pyam/utils.py
@@ -116,6 +116,11 @@ def read_pandas(path, default_sheet='data', *args, **kwargs):
         if len(xl.sheet_names) > 1 and 'sheet_name' not in kwargs:
             kwargs['sheet_name'] = default_sheet
         df = pd.read_excel(path, *args, **kwargs)
+
+        # remove unnamed and empty columns
+        empty_cols = [c for c in df.columns if str(c).startswith('Unnamed: ')
+                      and all(np.isnan(df[c]))]
+        df.drop(columns=empty_cols, inplace=True)
     return df
 
 
diff --git a/setup.py b/setup.py
index a19738654..ffcc4e359 100755
--- a/setup.py
+++ b/setup.py
@@ -13,7 +13,7 @@
 
 REQUIREMENTS = [
     'argparse',
-    'iam-units >= 2020.4.12',
+    'iam-units>=2020.4.12',
     'numpy',
     'requests',
     'pandas>=0.25.0',
diff --git a/tests/conftest.py b/tests/conftest.py
index d26002619..5138afb8a 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -189,6 +189,7 @@ def add_subannual(_data, name, value):
     df.set_meta('foo', 'string')
     yield df
 
+
 @pytest.fixture(scope="function")
 def reg_df():
     df = IamDataFrame(data=REG_DF)
diff --git a/tests/test_core.py b/tests/test_core.py
index b7825d0bd..53e47df63 100644
--- a/tests/test_core.py
+++ b/tests/test_core.py
@@ -97,9 +97,13 @@ def test_init_df_with_extra_col(test_pd_df):
 
     df = IamDataFrame(tdf)
 
+    # check that extra-cols attribute is set correctly
     assert df.extra_cols == [extra_col]
-    pd.testing.assert_frame_equal(df.timeseries().reset_index(),
-                                  tdf, check_like=True)
+
+    # check that timeseries data is as expected
+    obs = df.timeseries().reset_index()
+    exp = tdf[obs.columns]  # get the columns into the right order
+    pd.testing.assert_frame_equal(obs, exp)
 
 
 def test_init_empty_message(caplog):
diff --git a/tests/test_plotting.py b/tests/test_plotting.py
index 64556e376..802c8ce04 100644
--- a/tests/test_plotting.py
+++ b/tests/test_plotting.py
@@ -42,7 +42,7 @@ def test_line_plot(plot_df):
     _plot_df = copy.deepcopy(plot_df)
     _plot_df.set_meta(meta=[np.nan] * 4, name='test')
     fig, ax = plt.subplots(figsize=(8, 8))
-    _plot_df.line_plot(ax=ax, legend=True)
+    _plot_df.plot(ax=ax, legend=True)
     return fig
 
 
@@ -50,7 +50,7 @@ def test_line_plot_cmap(plot_df):
     # need to provide cmap and color both
     _plot_df = copy.deepcopy(plot_df)
     _plot_df.set_meta(meta=[np.nan] * 4, name='test')
-    pytest.raises(ValueError, _plot_df.line_plot, cmap='magma')
+    pytest.raises(ValueError, _plot_df.plot, cmap='magma')
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
@@ -58,35 +58,35 @@ def test_line_plot_cmap_color_arg(plot_df):
     _plot_df = copy.deepcopy(plot_df)
     _plot_df.set_meta(meta=[np.nan] * 4, name='test')
     fig, ax = plt.subplots(figsize=(8, 8))
-    _plot_df.line_plot(ax=ax, legend=True, cmap='magma', color='variable')
+    _plot_df.plot(ax=ax, legend=True, cmap='magma', color='variable')
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_line_plot_dict_legend(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.line_plot(ax=ax, legend=dict(loc='outside right'))
+    plot_df.plot(ax=ax, legend=dict(loc='outside right'))
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_line_plot_bottom_legend(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.line_plot(ax=ax, legend=dict(loc='outside bottom'))
+    plot_df.plot(ax=ax, legend=dict(loc='outside bottom'))
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_line_no_legend(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.line_plot(ax=ax, legend=False)
+    plot_df.plot(ax=ax, legend=False)
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_line_color(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.line_plot(ax=ax, color='model', legend=True)
+    plot_df.plot(ax=ax, color='model', legend=True)
     return fig
 
 
@@ -111,14 +111,14 @@ def test_line_PYAM_COLORS(plot_df):
     df = pyam.IamDataFrame(pd.concat(dfs))
     fig, ax = plt.subplots(figsize=(8, 8))
     with update_run_control(update):
-        df.line_plot(ax=ax, color='model', legend=True)
+        df.plot(ax=ax, color='model', legend=True)
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_line_color_fill_between(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.line_plot(ax=ax, color='model', fill_between=True, legend=True)
+    plot_df.plot(ax=ax, color='model', fill_between=True, legend=True)
     return fig
 
 
@@ -136,51 +136,51 @@ def test_line_color_fill_between_interpolate(plot_df):
     newdata = ['test_model1', 'test_scenario1', 'World', 'Primary Energy|Coal',
                'EJ/y', 2015, 3.50]
     df.data.loc[len(df.data) + 1] = newdata
-    df.line_plot(ax=ax, color='model', fill_between=True, legend=True)
+    df.plot(ax=ax, color='model', fill_between=True, legend=True)
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_line_color_final_ranges(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.line_plot(ax=ax, color='model', final_ranges=True, legend=True)
+    plot_df.plot(ax=ax, color='model', final_ranges=True, legend=True)
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_line_marker_legend(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.line_plot(ax=ax, marker='model', legend=True)
+    plot_df.plot(ax=ax, marker='model', legend=True)
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_line_rm_legend_label(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.line_plot(ax=ax, marker='model', linestyle='scenario', legend=True,
-                      rm_legend_label='marker')
+    plot_df.plot(ax=ax, marker='model', linestyle='scenario',
+                 legend=True, rm_legend_label='marker')
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_line_linestyle_legend(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.line_plot(ax=ax, linestyle='model', legend=True)
+    plot_df.plot(ax=ax, linestyle='model', legend=True)
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_line_single_color(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.line_plot(ax=ax, color='b', linestyle='model', legend=True)
+    plot_df.plot(ax=ax, color='b', linestyle='model', legend=True)
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_line_filter_title(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.filter(variable='Primary Energy|Coal').line_plot(
-        ax=ax, color='model', marker='scenario', legend=True)
+    plot_df.filter(variable='Primary Energy|Coal')\
+        .plot(ax=ax, color='model', marker='scenario', legend=True)
     return fig
 
 
@@ -188,7 +188,7 @@ def test_line_filter_title(plot_df):
 def test_line_update_rc(plot_df):
     with update_run_control({'color': {'model': {'test_model1': 'cyan'}}}):
         fig, ax = plt.subplots(figsize=(8, 8))
-        plot_df.line_plot(ax=ax, color='model', legend=True)
+        plot_df.plot(ax=ax, color='model', legend=True)
     return fig
 
 
@@ -197,7 +197,7 @@ def test_line_plot_1_var(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
     (plot_df
      .filter(model='test_model', scenario='test_scenario')
-     .line_plot(x='Primary Energy', y='year', ax=ax, legend=False)
+     .plot(x='Primary Energy', y='year', ax=ax, legend=False)
      )
     return fig
 
@@ -207,44 +207,36 @@ def test_line_plot_2_vars(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
     (plot_df
      .filter(model='test_model', scenario='test_scenario')
-     .line_plot(x='Primary Energy|Coal', y='Primary Energy', ax=ax, legend=False)
+     .plot(x='Primary Energy|Coal', y='Primary Energy', ax=ax, legend=False)
      )
     return fig
 
 
 def test_barplot_raises(plot_df):
-    pytest.raises(ValueError, plot_df.barplot)
+    pytest.raises(ValueError, plot_df.plot.bar)
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_barplot(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    (plot_df
-     .filter(variable='Primary Energy', model='test_model')
-     .barplot(ax=ax, bars='scenario')
-     )
+    plot_df.filter(variable='Primary Energy', model='test_model')\
+        .plot.bar(ax=ax, bars='scenario')
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_barplot_h(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    (plot_df
-     .filter(variable='Primary Energy', model='test_model')
-     .barplot(ax=ax, bars='scenario',
-               orient='h')
-     )
+    plot_df.filter(variable='Primary Energy', model='test_model')\
+        .plot.bar(ax=ax, bars='scenario', orient='h')
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_barplot_stacked(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    (plot_df
-     .filter(variable='Primary Energy', model='test_model')
-     .barplot(ax=ax, bars='scenario',
-               stacked=True)
-     )
+    plot_df.filter(variable='Primary Energy', model='test_model')\
+        .plot.bar(ax=ax, bars='scenario', stacked=True)
     return fig
 
 
@@ -253,8 +245,8 @@ def test_barplot_stacked_order_by_list(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
     plot_df\
         .filter(variable='Primary Energy', model='test_model')\
-        .barplot(ax=ax, bars='scenario', order=[2015, 2010],
-                 bars_order=['test_scenario1', 'test_scenario'], stacked=True)
+        .plot.bar(ax=ax, bars='scenario', order=[2015, 2010],
+                  bars_order=['test_scenario1', 'test_scenario'], stacked=True)
     return fig
 
 
@@ -266,7 +258,7 @@ def test_barplot_stacked_order_by_rc(plot_df):
         (
             plot_df
             .filter(variable='Primary Energy', model='test_model')
-            .barplot(ax=ax, bars='scenario', stacked=True)
+            .plot.bar(ax=ax, bars='scenario', stacked=True)
         )
     return fig
 
@@ -281,11 +273,9 @@ def test_barplot_stacked_net_line(plot_df):
         newdata = ['test_model1', 'test_scenario1', 'World',
                    'Primary Energy|foo', 'EJ/y', y, v]
         df.data.loc[len(df) + i] = newdata
-    (df
-     .filter(variable='Primary Energy|*', model='test_model1',
-             scenario='test_scenario1', region='World')
-     .barplot(ax=ax, bars='variable', stacked=True)
-     )
+    df.filter(variable='Primary Energy|*', model='test_model1',
+              scenario='test_scenario1', region='World')\
+        .plot.bar(ax=ax, bars='variable', stacked=True)
     plotting.add_net_values_to_barplot(ax, color='r')
     return fig
 
@@ -293,11 +283,8 @@ def test_barplot_stacked_net_line(plot_df):
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_barplot_title(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    (plot_df
-     .filter(variable='Primary Energy', model='test_model')
-     .barplot(ax=ax, bars='scenario',
-               title='foo')
-     )
+    plot_df.filter(variable='Primary Energy', model='test_model')\
+        .plot.bar(ax=ax, bars='scenario', title='foo')
     return fig
 
 
@@ -305,44 +292,38 @@ def test_barplot_title(plot_df):
 def test_barplot_rc(plot_df):
     with update_run_control({'color': {'scenario': {'test_scenario': 'black'}}}):
         fig, ax = plt.subplots(figsize=(8, 8))
-        (plot_df
-         .filter(variable='Primary Energy', model='test_model')
-         .barplot(ax=ax, bars='scenario')
-         )
+        plot_df.filter(variable='Primary Energy', model='test_model')\
+            .plot.bar(ax=ax, bars='scenario')
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_boxplot(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.boxplot(ax=ax)
+    plot_df.plot.box(ax=ax)
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_boxplot_hue(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.boxplot(ax=ax, by='model')
+    plot_df.plot.box(ax=ax, by='model')
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_pie_plot_labels(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    (plot_df
-     .filter(variable='Primary Energy', model='test_model', year=2010)
-     .pie_plot(ax=ax, category='scenario')
-     )
+    plot_df.filter(variable='Primary Energy', model='test_model', year=2010)\
+        .plot.pie(ax=ax, category='scenario')
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_pie_plot_legend(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    (plot_df
-     .filter(variable='Primary Energy', model='test_model', year=2010)
-     .pie_plot(ax=ax, category='scenario', labels=None, legend=True)
-     )
+    plot_df.filter(variable='Primary Energy', model='test_model', year=2010)\
+        .plot.pie(ax=ax, category='scenario', labels=None, legend=True)
     return fig
 
 
@@ -350,9 +331,10 @@ def test_pie_plot_legend(plot_df):
 def test_pie_plot_other(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
     with update_run_control(RC_TEST_DICT):
-        (plot_df
-         .filter(variable='Primary Energy', model='test_model', year=2010)
-         .pie_plot(ax=ax, category='scenario', cmap='viridis', title='foo')
+        (
+            plot_df
+            .filter(variable='Primary Energy', model='test_model', year=2010)
+            .plot.pie(ax=ax, category='scenario', cmap='viridis', title='foo')
          )
     return fig
 
@@ -360,21 +342,20 @@ def test_pie_plot_other(plot_df):
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_stackplot(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    (plot_df
-     .filter(variable='Primary Energy', model='test_model')
-     .stackplot(ax=ax, stack='scenario')
-     )
+    plot_df.filter(variable='Primary Energy', model='test_model')\
+        .plot.stack(ax=ax, stack='scenario')
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_stackplot_order_by_list(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    (plot_df
-     .filter(variable='Primary Energy', model='test_model')
-     .stackplot(ax=ax, stack='scenario',
-                order=['test_scenario1', 'test_scenario'])
-     )
+    (
+        plot_df
+        .filter(variable='Primary Energy', model='test_model')
+        .plot.stack(ax=ax, stack='scenario',
+                    order=['test_scenario1', 'test_scenario'])
+    )
     return fig
 
 
@@ -383,10 +364,8 @@ def test_stackplot_order_by_rc(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
     scen_list = ['test_scenario1']  # first list from rc, then alphabetical
     with update_run_control({'order': {'scenario': scen_list}}):
-        (plot_df
-         .filter(variable='Primary Energy', model='test_model')
-         .stackplot(ax=ax, stack='scenario')
-         )
+        plot_df.filter(variable='Primary Energy', model='test_model')\
+            .plot.stack(ax=ax, stack='scenario')
     return fig
 
 
@@ -394,10 +373,8 @@ def test_stackplot_order_by_rc(plot_df):
 def test_stackplot_other(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
     with update_run_control({'color': {'scenario': {'test_scenario': 'black'}}}):
-        (plot_df
-         .filter(variable='Primary Energy', model='test_model')
-         .stackplot(ax=ax, stack='scenario', cmap='viridis', title='foo')
-         )
+        plot_df.filter(variable='Primary Energy', model='test_model')\
+            .plot.stack(ax=ax, stack='scenario', cmap='viridis', title='foo')
     return fig
 
 
@@ -414,14 +391,14 @@ def test_stackplot_negative():
     fig, ax = plt.subplots(figsize=(8, 8))
     df = pyam.IamDataFrame(TEST_STACKPLOT_NEGATIVE, model='model_a',
                            scenario='scen_a', region='World', unit='foo')
-    df.stackplot(ax=ax, total=True)
+    df.plot.stack(ax=ax, total=True)
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_scatter(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.scatter(ax=ax, x='Primary Energy', y='Primary Energy|Coal')
+    plot_df.plot.scatter(ax=ax, x='Primary Energy', y='Primary Energy|Coal')
     return fig
 
 
@@ -438,16 +415,16 @@ def test_scatter_variables_with_meta_color(plot_df):
         criteria={'Primary Energy': {'lo': 5, 'year': 2010}},
         color='red'
     )
-    plot_df.scatter(ax=ax, x='Primary Energy', y='Primary Energy|Coal',
-                    color='foo')
+    plot_df.plot.scatter(ax=ax, x='Primary Energy', y='Primary Energy|Coal',
+                         color='foo')
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_scatter_with_lines(plot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_df.scatter(ax=ax, x='Primary Energy', y='Primary Energy|Coal',
-                    with_lines=True)
+    plot_df.plot.scatter(ax=ax, x='Primary Energy', y='Primary Energy|Coal',
+                         with_lines=True)
     return fig
 
 
@@ -458,7 +435,7 @@ def test_scatter_meta(plot_df):
                      .timeseries()[2010], name='Total')
     plot_df.set_meta(meta=plot_df.filter(variable='Primary Energy|Coal')
                      .timeseries()[2010], name='Coal')
-    plot_df.scatter(ax=ax, x='Total', y='Coal')
+    plot_df.plot.scatter(ax=ax, x='Total', y='Coal')
     return fig
 
 
@@ -472,36 +449,29 @@ def test_add_panel_label(plot_df):
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_stackplot_negative_emissions(plot_stackplot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_stackplot_df.stackplot(ax=ax)
+    plot_stackplot_df.plot.stack(ax=ax)
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_stackplot_negative_emissions_with_total(plot_stackplot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_stackplot_df.stackplot(ax=ax, total=True)
+    plot_stackplot_df.plot.stack(ax=ax, total=True)
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_stackplot_negative_emissions_kwargs_def_total(plot_stackplot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_stackplot_df.stackplot(
-        alpha=0.5,
-        total=True,
-        ax=ax,
-    )
+    plot_stackplot_df.plot.stack(ax=ax, alpha=0.5, total=True)
     return fig
 
 
 @pytest.mark.mpl_image_compare(**MPL_KWARGS)
 def test_stackplot_negative_emissions_kwargs_custom_total(plot_stackplot_df):
     fig, ax = plt.subplots(figsize=(8, 8))
-    plot_stackplot_df.stackplot(
-        alpha=0.5,
-        total={"color": "grey", "ls": "--", "lw": 2.0},
-        ax=ax,
-    )
+    total = {"color": "grey", "ls": "--", "lw": 2.0}
+    plot_stackplot_df.plot.stack(ax=ax, alpha=0.5, total=total)
     return fig
 
 
@@ -518,6 +488,5 @@ def test_stackplot_missing_zero_issue_266(plot_stackplot_df):
     ), model='model_a', scenario='scen_a', region='World', unit='some_unit')
 
     fig, ax = plt.subplots(figsize=(8, 8))
-    df.stackplot(ax=ax)
-
+    df.plot.stack(ax=ax)
     return fig