X轴比例尺与同一绘图上的2个数据集不匹配

Question

I have 2 datasets that I'm trying to plot on the same figure. They share a common column that I'm using for the X-axis, however one of my sets of data is collected annually and the other monthly so the number of data points in each set is significantly different.

Pyplot is not plotting the X values for each set where I would expect when I plot both sets on the same graph

When I plot just my annually collected data set I get:

When I plot just my monthly collected data set I get:

But when I plot the two sets overlayed (code below) I get:

tframe:

   10003   Date
0    257 201401
1    216 201402
2    417 201403
3    568 201404
4    768 201405
5    836 201406
6    798 201407
7    809 201408
8    839 201409
9    796 201410

tax_for_zip_data:

TAX BRACKET $1 under $25,000    ...       Date
2                       5740    ...     201301
0                       5380    ...     201401
1                       5320    ...     201501
3                       5030    ...     201601

So I did as wwii suggested in the comments and converted my Date columns to datetime objects:

tframe:

   10003       Date
0    257 2014-01-31
1    216 2014-02-28
2    417 2014-03-31
3    568 2014-04-30
4    768 2014-05-31
5    836 2014-06-30
6    798 2014-07-31
7    809 2014-08-31
8    839 2014-09-30
9    796 2014-10-31

tax_for_zip_data:

TAX BRACKET $1 under $25,000    ...           Date
2                       5740    ...     2013-01-31
0                       5380    ...     2014-01-31
1                       5320    ...     2015-01-31
3                       5030    ...     2016-01-31

But the dates are still plotting offset,

None of my data goes back to 2012- Jan 2013 is the earliest. The tax_for_zip_data are all offset by a year. If I plot just that set alone it plots properly.

fig, ax1 = plt.subplots(sharex = True)

color = "tab:red"
ax1.set_xlabel('Date')
ax1.set_ylabel('Trips', color = color)
tframe.plot(kind = 'line',x = 'Date', y = "10003", ax = ax1, color = color)
ax1.tick_params(axis = 'y', labelcolor = color)


ax2 = ax1.twinx()
color = "tab:blue"
ax2.set_ylabel('Num Returns', color = color)
tax_for_zip_data.plot(kind = 'line', x = 'Date', y = tax_for_zip_data.columns[:-1], ax = ax2)
ax2.tick_params(axis = 'y', labelcolor = color)

plt.show()

Answer 1

If you can make the DataFrame index a datetime index plotting is easier.

s = '''10003   Date
257   201401
216   201402
417   201403
568   201404
768   201405
836   201406
798   201407
809   201408
839   201409
796   201410
'''
df1 = pd.read_csv(io.StringIO(s), delimiter='\s{2,}',engine='python')
df1.index = pd.to_datetime(df1['Date'],format='%Y%m')

s = '''TAX BRACKET     $1 under $25,000           Date
2                       5740         201301
0                       5380         201401
1                       5320         201501
3                       5030         201601
'''
df2 = pd.read_csv(io.StringIO(s), delimiter='\s{2,}',engine='python')
df2.index = pd.to_datetime(df2['Date'],format='%Y%m')

You don't need to specify an argument for plot 's x parameter.

fig, ax1 = plt.subplots(sharex = True)

color = "tab:red"
ax1.set_xlabel('Date')
ax1.set_ylabel('Trips', color = color)
df1.plot(kind = 'line',y="10003", ax = ax1, color = color)
ax1.tick_params(axis = 'y', labelcolor = color)

ax2 = ax1.twinx()
color = "tab:blue"
ax2.set_ylabel('Num Returns', color = color)
df2.plot(kind = 'line', y='$1 under $25,000', ax = ax2)
ax2.tick_params(axis = 'y', labelcolor = color)

plt.show()
plt.close()

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