S Ringne S Ringne - 10 months ago 94
Python Question

Grouped Bar graph Pandas

i have a table in pandas dataframe 'df'

+--- -----+------------+-------------+----------+------------+-----------+
|avg_views| avg_orders | max_views |max_orders| min_views |min_orders |
| 23 | 123 | 135 | 500 | 3 | 1 |

What i am looking for now is to plot a grouped bar graph which shows me
(avg,max,min) of views and orders in one single bar chart.

i.e on x axis there would be Views and orders seperated by a distance
and 3 bars of (avg,max,min) for views and similarly for orders.

i have attached a sample bar graph image, just to know how the bar graph should look.

just sample: green color should be for avg, yellow for max and pin
green color should be for avg, yellow for max and pink for avg

i took the following code from setting spacing between grouped bar plots in matplotlib but it is not working for me

plt.figure(figsize=(13,7), dpi=300)

groups = [[23,135,3],
group_labels = ["views", "orders"]
num_items = len(group_labels)
ind = np.arange(num_items)
margin = 0.05
width = (1.-2.*margin)/num_items

s = plt.subplot(1,1,1)
for num, vals in enumerate(groups):
print "plotting: ", vals
# The position of the xdata must be calculated for each of the two data series
xdata = ind+margin+(num*width)
# Removing the "align=center" feature will left align graphs, which is what
# this method of calculating positions assumes
gene_rects = plt.bar(xdata, vals, width)

Answer Source

Using pandas:

import pandas as pd

# convert data to pandas dataframe
df = pd.DataFrame(groups, index=group_labels).T

# plot
    [df.mean().rename('average'), df.min().rename('min'), df.max().rename('max')],