Pandas: multiple bar plot from aggregated columns

Question

In python pandas I have create a dataframe with one value for each year and two subclasses - i.e., one metric for a parameter triplet

import pandas, requests, numpy
import matplotlib.pyplot as plt

df

       Metric    Tag_1  Tag_2  year
0     5770832  FOOBAR1  name1  2008
1     7526436  FOOBAR1    xyz  2008
2    33972652  FOOBAR1  name1  2009
3    17491416  FOOBAR1    xyz  2009
...
16    6602920  baznar2  name1  2008
17       6608  baznar2    xyz  2008
...
30  142102944  baznar2  name1  2015
31          0  baznar2    xyz  2015

I would like to produce a bar plot with metrics as y-values over x=(year,Tag_1,Tag_2) and sorting primarily for years and secondly for tag_1 and color the bars depending on tag_1. Something like

(2008,FOOBAR,name1)   --> 5770832  *RED*
(2008,baznar2,name1)  --> 6602920  *BLUE*
(2008,FOOBAR,xyz)     --> 7526436  *RED*
(2008,baznar2,xyz)    --> ...      *BLUE*
(2008,FOOBAR,name1)   --> ...      *RED*

I tried starting with a grouping of columns like

df.plot.bar(x=['year','tag_1','tag_2']

but have not found a way to separate selections into two bar sets next to each other.

You'll be more likely to get an answer if we can create an example dataframe by copy and pasting. — andrew
– andrew, Commented May 27, 2016 at 16:31

andrew · Accepted Answer · 2016-05-27 16:56:51Z

1

This should get you on your way:

df = pd.read_csv('path_to_file.csv')

# Group by the desired columns
new_df = df.groupby(['year', 'Tag_1', 'Tag_2']).sum()
# Sort descending
new_df.sort('Metric', inplace=True)


# Helper function for generation sequence of 'r' 'b' colors
def get_color(i):
    if i%2 == 0:
        return 'r'
    else:
        return 'b'

colors = [get_color(j) for j in range(new_df.shape[0])]

# Make the plot
fig, ax = plt.subplots()
ind = np.arange(new_df.shape[0])
width = 0.65
a = ax.barh(ind, new_df.Metric, width, color = colors) # plot a vals
ax.set_yticks(ind + width)  # position axis ticks
ax.set_yticklabels(new_df.index.values)  # set them to the names
fig.tight_layout()
plt.show()

answered May 27, 2016 at 16:56

andrew

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Comments

MaxU - stand with Ukraine · Accepted Answer · 2016-05-27 20:29:03Z

1

you can also do it this way:

fig, ax = plt.subplots()
df.groupby(['year', 'Tag_1', 'Tag_2']).sum().plot.barh(color=['r','b'], ax=ax)
fig.tight_layout()
plt.show()

PS if don't like scientific notation you can get rid of it:

ax.get_xaxis().get_major_formatter().set_scientific(False)

edited May 27, 2016 at 20:29

answered May 27, 2016 at 20:10

MaxU - stand with Ukraine

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