3

I have plots like this 

fig = plt.figure()
desire_salary = (df[(df['inc'] <= int(salary_people))])
print desire_salary
# Create the pivot_table
result = desire_salary.pivot_table('city', 'cult', aggfunc='count')

# plot it in a separate step. this returns the matplotlib axes
ax = result.plot(kind='bar', alpha=0.75, rot=0, label="Presence / Absence of cultural centre")

ax.set_xlabel("Cultural centre")
ax.set_ylabel("Frequency")
ax.set_title('The relationship between the wage level and the presence of the cultural center')
plt.show()

I want to add this to subplot. I try 

fig, ax = plt.subplots(2, 3)
...
ax = result.add_subplot()

but it returns AttributeError: 'Series' object has no attribute 'add_subplot'`. How can I check this error?

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Arseniy Krupenin
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  • do you want to plot 6 plots? – MaxU - stand with Ukraine Jun 13 '16 at 20:57
  • @MaxU, Yes, I want to add 6 plot to one. I have that separately, but I want to unite that – Arseniy Krupenin Jun 13 '16 at 20:59
  • check the link, i've provided in my answer - i was doing there almost the same (i was using seaborn.boxplot instead of barplot, that you want to use) – MaxU - stand with Ukraine Jun 13 '16 at 21:01
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    Try always to provide a [Minimal, Complete, and Verifiable example](http://stackoverflow.com/help/mcve) when asking questions. In case of _pandas_ questions please provide sample _input_ and _output_ data sets (5-7 rows in CSV/dict/JSON/Python code format _as text_, so one could use it when coding an answer for you). This will help to avoid _situations_ like: `your code isn't working for me` or `it doesn't work with my data`, etc. – MaxU - stand with Ukraine Jun 13 '16 at 21:05

2 Answers2

7

matplotlib.pyplot has the concept of the current figure and the current axes. All plotting commands apply to the current axes.

import matplotlib.pyplot as plt

fig, axarr = plt.subplots(2, 3)     # 6 axes, returned as a 2-d array

#1 The first subplot
plt.sca(axarr[0, 0])                # set the current axes instance to the top left
# plot your data
result.plot(kind='bar', alpha=0.75, rot=0, label="Presence / Absence of cultural centre")

#2 The second subplot
plt.sca(axarr[0, 1])                # set the current axes instance 
# plot your data

#3 The third subplot
plt.sca(axarr[0, 2])                # set the current axes instance 
# plot your data

Demo:

enter image description here

The source code,

import matplotlib.pyplot as plt
fig, axarr = plt.subplots(2, 3, sharex=True, sharey=True)     # 6 axes, returned as a 2-d array

for i in range(2):
    for j in range(3):
        plt.sca(axarr[i, j])                        # set the current axes instance 
        axarr[i, j].plot(i, j, 'ro', markersize=10) # plot 
        axarr[i, j].set_xlabel(str(tuple([i, j])))  # set x label
        axarr[i, j].get_xaxis().set_ticks([])       # hidden x axis text
        axarr[i, j].get_yaxis().set_ticks([])       # hidden y axis text

plt.show()
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2

result is of pandas.Series type, which doesn't have add_subplot() method.

use fig.add_subplot(...) instead

Here is an example (using seaborn module):

labels = df.columns.values
fig, axes = plt.subplots(nrows = 3, ncols = 4, gridspec_kw =  dict(hspace=0.3),figsize=(12,9), sharex = True, sharey=True)
targets = zip(labels, axes.flatten())
for i, (col,ax) in enumerate(targets):
    sns.boxplot(data=df, ax=ax, color='green', x=df.index.month, y=col)

You can use pandas plots instead of seaborn

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