How to plot data after groupby

Question

I have a data frame similar to this

import pandas as pd
df = pd.DataFrame([['1','3','1','2','3','1','2','2','1','1'], ['ONE','TWO','ONE','ONE','ONE','TWO','ONE','TWO','ONE','THREE']]).T
df.columns = [['age','data']]
print(df)   #printing dataframe.

I performed the groupby function on it to get the required output.

df['COUNTER'] =1       #initially, set that counter to 1.
group_data = df.groupby(['age','data'])['COUNTER'].sum() #sum function
print(group_data)

now i want to plot the out using matplot lib. Please help me with it.. I am not able to figure how to start and what to do. I want to plot using the counter value and something similar to bar graph

Answer 1

Try:

group_data = group_data.reset_index()

in order to get rid of the multiple index that the groupby() has created for you.

Your print(group_data) will give you this:

In [24]: group_data = df.groupby(['age','data'])['COUNTER'].sum() #sum function

In [25]: print(group_data)
age  data 
1    ONE      3
     THREE    1
     TWO      1
2    ONE      2
     TWO      1
3    ONE      1
     TWO      1
Name: COUNTER, dtype: int64

Whereas, reseting will 'simplify' the new index:

In [26]: group_data = group_data.reset_index()

In [27]: group_data
Out[27]: 
  age   data  COUNTER
0   1    ONE        3
1   1  THREE        1
2   1    TWO        1
3   2    ONE        2
4   2    TWO        1
5   3    ONE        1
6   3    TWO        1

Then depending on what it is exactly that you want to plot, you might want to take a look at the Matplotlib docs

EDIT

I now read more carefully that you want to create a 'bar' chart.

If that is the case then I would take a step back and not use reset_index() on the groupby result. Instead, try this:

In [46]: fig = group_data.plot.bar()

In [47]: fig.figure.show()

I hope this helps

Answer 2

Try with this:

# This is a great tool to add plots to jupyter notebook
% matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt

# Params get plot bigger
plt.rcParams["axes.labelsize"] = 16
plt.rcParams["xtick.labelsize"] = 14
plt.rcParams["ytick.labelsize"] = 14
plt.rcParams["legend.fontsize"] = 12
plt.rcParams["figure.figsize"] = [15, 7]

df = pd.DataFrame([['1','3','1','2','3','1','2','2','1','1'], ['ONE','TWO','ONE','ONE','ONE','TWO','ONE','TWO','ONE','THREE']]).T
df.columns = [['age','data']]
df['COUNTER'] = 1

group_data = df.groupby(['age','data']).sum()[['COUNTER']].plot.bar(rot = 90) # If you want to rotate labels from x axis
_ = group_data.set(xlabel = 'xlabel', ylabel = 'ylabel'), group_data.legend(['Legend']) # you can add labels and legend