Pandas DataFrame Plot - Line Chart

visibility 2,363 event 2020-04-04 access_time 2 years ago language English
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Pandas DataFrame Plot - Line Chart

This article provides examples about plotting line chart using pandas.DataFrame.plot function.

Prerequisites

The data I'm going to use is the same as the other article Pandas DataFrame Plot - Bar Chart. I'm also using Jupyter Notebook to plot them.

The DataFrame has 9 records:

DATETYPESALES
02020-01-01TypeA1000
12020-01-01TypeB200
22020-01-01TypeC300
32020-02-01TypeA700
42020-02-01TypeB400
52020-02-01TypeC500
62020-03-01TypeA300
72020-03-01TypeB900
82020-03-01TypeC100


Line chart plot

df.groupby(['DATE','TYPE']).sum().unstack().plot(kind='line',y='SALES')

The output of the plotting:

2020040412603-image.png

Change marker

The following code snippet changes marker to circle. Refer to matplotlib documentation about all the options you could choose. 

df.groupby(['DATE','TYPE']).sum().unstack().plot(kind='line',y='SALES', marker='o')

2020040413315-image.png

Cumulative line chart

Similar as the bar chart plotting, we can also plot a cumulative line chart.

df.groupby(['DATE','TYPE']).sum().groupby(level=[1]).cumsum().unstack().plot(kind='line',y='SALES', stacked = True)

2020040413423-image.png

X-axis labels

In the above charts, X-axis labels are very crowded. There are multiple ways to fix it. One of the approaches is to use formatter and also set major locator. 

The code snippet looks like the following

import matplotlib
import matplotlib.dates as mdates
from matplotlib.dates import DateFormatter

df_unstack = df.groupby(['DATE','TYPE']).sum().groupby(level=[1]).cumsum().unstack()
plt =df_unstack.plot(kind='line',y='SALES', marker='o', stacked = True)

date_form = DateFormatter("%Y-%m")
plt.xaxis.set_major_formatter(date_form)
plt.xaxis.set_major_locator(mdates.MonthLocator(interval=1))

Chart looks like this:

2020040422038-image.png

Similarly for the non-cumulative one, you can also set up the major locator:

import matplotlib
import matplotlib.dates as mdates
from matplotlib.dates import DateFormatter

df_unstack = df.groupby(['DATE','TYPE']).sum().unstack()
plt =df_unstack.plot(kind='line',y='SALES', marker='o', stacked = True)

date_form = DateFormatter("%Y-%m")
plt.xaxis.set_major_formatter(date_form)
plt.xaxis.set_major_locator(mdates.MonthLocator(interval=1))

Output looks like the following screenshot:

2020040422150-image.png

info Last modified by Raymond 2 years ago copyright This page is subject to Site terms.
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