AttributeError: Unknown property column in Geopandas plotting of events in zipcode shp file - python-3.x

Question

I am trying to create a Choropleth map showing fire incidents throughout a county in NC. I have the data in a Dataframe and last night I was able to export maps. The only problem was that the data exported was not accurate--so there was a problem with my code. I think I managed to fix that, by merging the shapefiles and data dataframes together, but now, when I run the portion that creates the map, I get AttributeError: Unknown property column Full message:
AttributeError Traceback (most recent call last)
<ipython-input-74-61a60b41abbe> in <module>()
13 # create map
14
---> 15 merged_df.plot(column=variable, cmap='Reds', linewidth=0.8, ax=ax, edgecolor='0.8');
16
17 ax.axis('off')
~\Anaconda3\lib\site-packages\pandas\plotting\_core.py in __call__(self, x, y, kind, ax, subplots, sharex, sharey, layout, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, secondary_y, sort_columns, **kwds)
2939 fontsize=fontsize, colormap=colormap, table=table,
2940 yerr=yerr, xerr=xerr, secondary_y=secondary_y,
-> 2941 sort_columns=sort_columns, **kwds)
2942 __call__.__doc__ = plot_frame.__doc__
2943
~\Anaconda3\lib\site-packages\pandas\plotting\_core.py in plot_frame(data, x, y, kind, ax, subplots, sharex, sharey, layout, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, secondary_y, sort_columns, **kwds)
1975 yerr=yerr, xerr=xerr,
1976 secondary_y=secondary_y, sort_columns=sort_columns,
-> 1977 **kwds)
1978
1979
~\Anaconda3\lib\site-packages\pandas\plotting\_core.py in _plot(data, x, y, subplots, ax, kind, **kwds)
1802 plot_obj = klass(data, subplots=subplots, ax=ax, kind=kind, **kwds)
1803
-> 1804 plot_obj.generate()
1805 plot_obj.draw()
1806 return plot_obj.result
~\Anaconda3\lib\site-packages\pandas\plotting\_core.py in generate(self)
258 self._compute_plot_data()
259 self._setup_subplots()
--> 260 self._make_plot()
261 self._add_table()
262 self._make_legend()
~\Anaconda3\lib\site-packages\pandas\plotting\_core.py in _make_plot(self)
983 stacking_id=stacking_id,
984 is_errorbar=is_errorbar,
--> 985 **kwds)
986 self._add_legend_handle(newlines[0], label, index=i)
987
~\Anaconda3\lib\site-packages\pandas\plotting\_core.py in _plot(cls, ax, x, y, style, column_num, stacking_id, **kwds)
999 cls._initialize_stacker(ax, stacking_id, len(y))
1000 y_values = cls._get_stacked_values(ax, stacking_id, y, kwds['label'])
-> 1001 lines = MPLPlot._plot(ax, x, y_values, style=style, **kwds)
1002 cls._update_stacker(ax, stacking_id, y)
1003 return lines
~\Anaconda3\lib\site-packages\pandas\plotting\_core.py in _plot(cls, ax, x, y, style, is_errorbar, **kwds)
613 else:
614 args = (x, y)
--> 615 return ax.plot(*args, **kwds)
616
617 def _get_index_name(self):
~\Anaconda3\lib\site-packages\matplotlib\__init__.py in inner(ax, data, *args, **kwargs)
1808 "the Matplotlib list!)" % (label_namer, func.__name__),
1809 RuntimeWarning, stacklevel=2)
-> 1810 return func(ax, *args, **kwargs)
1811
1812 inner.__doc__ = _add_data_doc(inner.__doc__,
~\Anaconda3\lib\site-packages\matplotlib\axes\_axes.py in plot(self, scalex, scaley, *args, **kwargs)
1609 kwargs = cbook.normalize_kwargs(kwargs, mlines.Line2D._alias_map)
1610
-> 1611 for line in self._get_lines(*args, **kwargs):
1612 self.add_line(line)
1613 lines.append(line)
~\Anaconda3\lib\site-packages\matplotlib\axes\_base.py in _grab_next_args(self, *args, **kwargs)
391 this += args[0],
392 args = args[1:]
--> 393 yield from self._plot_args(this, kwargs)
394
395
~\Anaconda3\lib\site-packages\matplotlib\axes\_base.py in _plot_args(self, tup, kwargs)
381 "with non-matching shapes is deprecated.")
382 for j in range(max(ncx, ncy)):
--> 383 seg = func(x[:, j % ncx], y[:, j % ncy], kw, kwargs)
384 ret.append(seg)
385 return ret
~\Anaconda3\lib\site-packages\matplotlib\axes\_base.py in _makeline(self, x, y, kw, kwargs)
286 default_dict = self._getdefaults(None, kw)
287 self._setdefaults(default_dict, kw)
--> 288 seg = mlines.Line2D(x, y, **kw)
289 return seg
290
~\Anaconda3\lib\site-packages\matplotlib\lines.py in __init__(self, xdata, ydata, linewidth, linestyle, color, marker, markersize, markeredgewidth, markeredgecolor, markerfacecolor, markerfacecoloralt, fillstyle, antialiased, dash_capstyle, solid_capstyle, dash_joinstyle, solid_joinstyle, pickradius, drawstyle, markevery, **kwargs)
408 # update kwargs before updating data to give the caller a
409 # chance to init axes (and hence unit support)
--> 410 self.update(kwargs)
411 self.pickradius = pickradius
412 self.ind_offset = 0
~\Anaconda3\lib\site-packages\matplotlib\artist.py in update(self, props)
914
915 with cbook._setattr_cm(self, eventson=False):
--> 916 ret = [_update_property(self, k, v) for k, v in props.items()]
917
918 if len(ret):
~\Anaconda3\lib\site-packages\matplotlib\artist.py in <listcomp>(.0)
914
915 with cbook._setattr_cm(self, eventson=False):
--> 916 ret = [_update_property(self, k, v) for k, v in props.items()]
917
918 if len(ret):
~\Anaconda3\lib\site-packages\matplotlib\artist.py in _update_property(self, k, v)
910 func = getattr(self, 'set_' + k, None)
911 if not callable(func):
--> 912 raise AttributeError('Unknown property %s' % k)
913 return func(v)
914
AttributeError: Unknown property column
I have no idea how to fix this. I've googled and tried changing the dtype from float to int, tried different columns, but no change. I don't understand because it worked last night, but didn't work when I tried to run it today before making changes. Thank you in advance for any help. Below is the bulk of my code that contains the data frame and mapping, everything else is just getting data from csvs:
import pandas as pd
import numpy as np
#import googlemaps
import gmaps
import gmaps.datasets
import geopandas as gpd
#import matplotlib as plt
import matplotlib.pyplot as plt
import os
import plotly.plotly as py
import plotly.tools as tls
This is what the merged dataframe looks like:
OBJECTID_x int64
ZIPNUM float64
address object
address2 object
apt_room object
arrive_date_time object
cleared_date_time object
dispatch_date_time object
exposure int64
incident_number object
incident_type int64
incident_type_description object
platoon object
station float64
Longitude object
Latitude object
Year int64
Date object
Arr Time object
Seconds float64
Incident object
OBJECTID_y int64
ZIPNAME object
ZIPCODE object
NAME object
SHAPEAREA float64
SHAPELEN float64
LAST_EDITE object
geometry object
dtype: object
# set a variable that will call column to visualise on the map
variable = 'ZIPNUM'
# set the range for the choropleth
vmin, vmax = 50, 2000
# create figure and axes for Matplotlib
fig, ax = plt.subplots(1, figsize=(15, 15))
# create map
merged_df.plot(column=variable, cmap='Reds', linewidth=0.8, ax=ax, edgecolor='0.8');
ax.axis('off')
ax.set_title('Fire Incident Rate in Wake County', fontdict={'fontsize': '25', 'fontweight' : '3'})
# Create colorbar as a legend
sm = plt.cm.ScalarMappable(cmap='Reds', norm=plt.Normalize(vmin=vmin, vmax=vmax))
# empty array for the data range
sm._A = []
# add the colorbar to the figure
cbar = fig.colorbar(sm)
ax.annotate('2008-2018',
xy=(0.001, .225), xycoords='figure fraction',
horizontalalignment='left', verticalalignment='top',
fontsize=35)
fig.savefig("Fire Incident Rate in Wake County 2008-2018.png", dpi=300)

Answer 1

The problem is that you are trying to use column as a keyword argument. Since you want to plot the 'ZIPNUM' column of the DataFrame, which you store in a variable called variable, you can just pass it as a positional argument to plot(). If you want to plot a relationship between two variables, you can use keyword arguments merged_df.plot(x=variable1, y=variable2)
For you case, you can use
variable = 'ZIPNUM'
merged_df.plot(variable, cmap='Reds', linewidth=0.8, ax=ax, edgecolor='0.8');
EDIT (based on comments)
You should use markeredgecolor only if you use marker for plotting. edgecolor is not the correct keyword. Moreover, you are assigning a number (string) as color which is again incorrect. Below is a simple example.
df = pd.DataFrame([[1, 2], [3, 4], [5, 6], [7, 8]], columns=["A", "B"])
column='A'
df.plot(column, linewidth=0.8, color='r', marker ='o', markeredgewidth=2,
markeredgecolor='blue')