Plotting a grouped pandas dataframe

Question

I spent a few hours searching for an answer, but I can't seem to get one.

Long story short, I have a dataframe. The following code will produce the dataframe in question (albeit anonymised with random numbers):

variable1 = ["Attribute 1","Attribute 1","Attribute 1","Attribute 1","Attribute 1","Attribute 1","Attribute 2","Attribute 2",
         "Attribute 2","Attribute 2","Attribute 2","Attribute 2","Attribute 3","Attribute 3","Attribute 3","Attribute 3",
         "Attribute 3","Attribute 3","Attribute 4","Attribute 4","Attribute 4","Attribute 4","Attribute 4","Attribute 4",
         "Attribute 5","Attribute 5","Attribute 5","Attribute 5","Attribute 5","Attribute 5"]


variable2 = ["Property1","Property2","Property3","Property4","Property5","Property6","Property1","Property2","Property3",
         "Property4","Property5","Property6","Property1","Property2","Property3",
         "Property4","Property5","Property6","Property1","Property2","Property3","Property4",
         "Property5","Property6","Property1","Property2","Property3","Property4","Property5","Property6"]

number = [93,224,192,253,186,266,296,100,135,169,373,108,211,194,164,375,211,71,120,334,59,164,348,50,249,18,251,343,172,41]

bar = pd.DataFrame({"variable1":variable1, "variable2":variable2, "number":number})

bar_grouped = bar.groupby(["variable1","variable2"]).sum()

The outcome should look like:

And the second one:

I have been trying to plot them with a bar chart and having the Properties as the groups and the different Attributes as the bars. Similar to this (plotted in Excel manually though). I would prefer to do it in the grouped datafarme, as to be able to plot with different groupings without the need to reset the index each time.

I hope this is clear.

Any help on this is hugely appreciated.

Thanks! :)

Try bar_grouped['number'].unstack(0).plot(kind='bar')

Chris Adams
– Chris Adams

2019-08-06 12:49:42 +00:00
Commented Aug 6, 2019 at 12:49 — Chris Adams
– Chris Adams, Commented Aug 6, 2019 at 12:49

user3483203 · Accepted Answer · 2019-08-06 13:04:40Z

4

I wouldn't bother creating your groupby result (since you aren't aggregating anything). This is a pivot

bar.pivot('variable2', 'variable1', 'number').plot(kind='bar')

plt.tight_layout()
plt.show()

If aggregation is required, you can still start with your bar and use pivot_table

bar.pivot_table(index='variable2', columns='variable1', values='number', aggfunc='sum')

edited Aug 6, 2019 at 13:04

answered Aug 6, 2019 at 12:59

user3483203

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1 Comment

Alex Rpd Over a year ago

Aggregation is required as this is only part of a larger DataFrame that has more values that can bee aggregated, eventually, so thanks for that! :)

Chris Adams · Accepted Answer · 2019-08-06 12:53:58Z

3

Use unstack first:

bar_grouped['number'].unstack(0).plot(kind='bar')

[out]

answered Aug 6, 2019 at 12:53

Chris Adams

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Comments

Amit · Accepted Answer · 2019-08-06 13:44:43Z

Below code will do what you trying to establish :

import numpy as np
import matplotlib.pyplot as plt

# set width of bar
barWidth = 0.25
f = plt.figure(figsize=(15,8))

bars={}
bar_pos={}
for i,proprty in enumerate(bar_grouped.unstack().columns.droplevel(0).tolist()):
    bars[i] = bar_grouped.unstack()['number',proprty].tolist()
    if(i==0):
        bar_pos[i]=2*np.arange(len(bars1))
    else:
        bar_pos[i]=[x + barWidth for x in bar_pos[i-1]] 
    plt.bar(bar_pos[i], bars[i], width=barWidth, edgecolor='white', label=proprty, figure=f)

# Add xticks on the middle of the group bars
plt.xlabel('group', fontweight='bold')
plt.xticks([2*r + 2*barWidth for r in range(len(bars[0]))], bar_grouped.unstack().index.tolist())
# plt.figure(figsize=(10,5))

# Create legend & Show graphic
plt.legend(loc=0)
plt.show()

I took the solution from here and modified it to fit your need. Hope this helps!

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