Display two bar charts one by one in MATPLOTLIB - python

I am plotting bar charts using pivot tables. I have two independent pivot tables and need to produce two bar charts side-by-side and save it as a PNG image. Using this code, the chart is generated but it won't display as expected.
What I tried:
# Plotting Activity Begins
fig = plt.figure()
ax1 = fig.add_subplot(1, 2, 1)
ax2 = fig.add_subplot(2, 2, 1)
vig = task_frame.plot(kind="bar", figsize=(8, 6), stacked=True, width=0.3, rot=20)
print "ax1",ax1
print "vig",vig
vicky = issue_frame.plot(kind="bar", figsize=(8, 6), stacked=True, width=0.3, rot=90)
print "ax2",ax2
print "vicky",vicky
plt.ylim((0, 10))
plt.rcParams.update({'font.size': 10})
plt.savefig("/tmp/" + str(current_date) + ".png")
My print statement values:
ax1 Axes(0.125,0.1;0.352273x0.8)
vig Axes(0.125,0.1;0.775x0.8)
ax2 Axes(0.125,0.536364;0.352273x0.363636)
vicky Axes(0.125,0.1;0.775x0.8)
How can I display the charts as side-by-side pictures in a single image? Where should I assign the ax1 and ax2 value?


When you plot try to add axes instance to plot function, like here:
...
fig = plt.figure()
ax1 = fig.add_subplot(1, 2, 1)
ax2 = fig.add_subplot(2, 2, 1)
task_frame.plot(..., ax=ax1)
issue_frame.plot(..., ax=ax2)
...

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You can customize GridSpec options, passing them to subplots, with the key gridspec_kw:
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I would like to arrange four Seaborn plots in a 2 x 2 grid. I tried the following code but I got an exception. I would also like to know how to set titles and xlabel, ylabel in the subplots and a title for the overall grid plot.
Some toy data:
df
'{"age":{"76":33,"190":30,"255":36,"296":27,"222":19,"147":39,"127":23,"98":24,"168":29,"177":39,"197":27,"131":36,"36":30,"219":28,"108":38,"198":34,"40":32,"246":24,"109":26,"117":47,"20":26,"113":24,"279":35,"120":35,"7":26,"119":28,"272":24,"66":28,"87":28,"133":28},"Less_than_College":{"76":1,"190":1,"255":0,"296":1,"222":1,"147":1,"127":0,"98":0,"168":1,"177":1,"197":0,"131":1,"36":0,"219":0,"108":0,"198":0,"40":0,"246":0,"109":1,"117":1,"20":0,"113":0,"279":0,"120":0,"7":0,"119":1,"272":0,"66":1,"87":0,"133":0},"college":{"76":0,"190":0,"255":0,"296":0,"222":0,"147":0,"127":1,"98":1,"168":0,"177":0,"197":1,"131":0,"36":1,"219":1,"108":0,"198":1,"40":1,"246":0,"109":0,"117":0,"20":1,"113":1,"279":0,"120":1,"7":1,"119":0,"272":0,"66":0,"87":1,"133":1},"Bachelor":{"76":0,"190":0,"255":1,"296":0,"222":0,"147":0,"127":0,"98":0,"168":0,"177":0,"197":0,"131":0,"36":0,"219":0,"108":1,"198":0,"40":0,"246":1,"109":0,"117":0,"20":0,"113":0,"279":1,"120":0,"7":0,"119":0,"272":1,"66":0,"87":0,"133":0},"terms":{"76":30,"190":15,"255":30,"296":30,"222":30,"147":15,"127":15,"98":15,"168":30,"177":30,"197":15,"131":30,"36":15,"219":15,"108":30,"198":7,"40":30,"246":15,"109":15,"117":15,"20":15,"113":15,"279":15,"120":15,"7":15,"119":30,"272":15,"66":30,"87":30,"133":15},"Principal":{"76":1000,"190":1000,"255":1000,"296":1000,"222":1000,"147":800,"127":800,"98":800,"168":1000,"177":1000,"197":1000,"131":1000,"36":1000,"219":800,"108":1000,"198":1000,"40":1000,"246":1000,"109":1000,"117":1000,"20":1000,"113":800,"279":800,"120":800,"7":800,"119":1000,"272":1000,"66":1000,"87":1000,"133":1000}}'
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ax = fig.add_subplot(2, 2, 1)
ax.sns.distplot(df.Principal)
ax = fig.add_subplot(2, 2, 2)
ax.sns.distplot(df.terms)
ax = fig.add_subplot(2, 2, 3)
ax.sns.barplot(data = df[['Less_than_College', 'college', 'Bachelor', ]])
ax = fig.add_subplot(2, 2, 4)
ax.sns.boxplot(data = df['age'])
plt.show()
AttributeError: 'AxesSubplot' object has no attribute 'sns'

ax is matplotlib object that do not have sns attribute, because of this you are getting error. sns is seaborn object. If you want to use ax object with seaborn plot for your case pass parameter ax=ax in seaborn object as follows:
fig = plt.figure()
fig.subplots_adjust(hspace=0.4, wspace=0.4)
ax = fig.add_subplot(2, 2, 1)
sns.distplot(df.Principal,ax=ax)
ax = fig.add_subplot(2, 2, 2)
sns.distplot(df.terms,ax=ax)
ax = fig.add_subplot(2, 2, 3)
sns.barplot(data = df[['Less_than_College', 'college', 'Bachelor']],ax=ax)
ax.set_xticklabels(ax.get_xticklabels(), rotation=90)
ax = fig.add_subplot(2, 2, 4)
sns.boxplot(df['age'],ax=ax)
plt.show()
The plot looks like this.

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