Plotting Pandas Dataframe From Pivot

I am trying to plot a line graph comparing the Murder Rates of particular States through the years 1960-1962 using Pandas in a Jupyter Notebook. A little context about where I am

Solution 1:

Given a dataframe in a long (tidy) format, pandas.DataFrame.pivot is used to transform to a wide format, which can be plotted directly with pandas.DataFrame.plot

Tested in python 3.8.11, pandas 1.3.3, matplotlib 3.4.3

import numpy as np
import pandas as pd

control_1960_to_1962 = pd.DataFrame({
    'State': np.repeat(['Alaska', 'Maine', 'Michigan', 'Minnesota', 'Wisconsin'], 3),
    'Year': [1960, 1961, 1962]*5,
    'Murder Rate': [10.2, 11.5, 4.5, 1.7, 1.6, 1.4, 4.5, 4.1, 3.4, 1.2, 1.0, .9, 1.3, 1.6, .9]
})

df = control_1960_to_1962.pivot(index='Year', columns='State', values='Murder Rate')

# display(df)
State  Alaska  Maine  Michigan  Minnesota  Wisconsin
Year                                                
196010.21.74.51.21.3196111.51.64.11.01.619624.51.43.40.90.9

The plots

You can tell Pandas (and through it the matplotlib package that actually does the plotting) what xticks you want explicitly:

ax = df.plot(xticks=df.index, ylabel='Murder Rate')

Output:

ax is a matplotlib.axes.Axes object, and there are many, many customizations you can make to your plot through it.

Here's how to plot with the States on the x axis:

ax = df.T.plot(kind='bar', ylabel='Murder Rate')

Output:

Solution 2:

try this you can explore more

   pip install pivottablejs

   import pandas as pd
   import numpy as np
   from pivottablejs import pivot_ui
   df = pd.DataFrame({
      'State': np.repeat(['Alaska', 'Maine', 'Michigan', 'Minnesota','Wisconsin'], 3),
      'Year': [1960, 1961, 1962]*5,
      'Murder Rate': [10.2, 11.5, 4.5, 1.7, 1.6, 1.4, 4.5, 4.1, 3.4, 1.2, 1.0, .9, 1.3, 1.6, .9]})

pivot_ui(df)