Python

#plot data
fig, ax = plt.subplots(figsize=(15,7))
data.groupby(['date','type']).count()['amount'].plot(ax=ax)

df.groupby('year').case_status.value_counts().unstack(0).plot.barh()

df.groupby(['tags_0', 'gender']).gender.count().unstack().plot(kind='barh', legend=False, color=['r', 'g', 'b'])

# plot data
fig, ax = plt.subplots(figsize=(15,7))
# use unstack()
data.groupby(['date','type']).count()['amount'].unstack().plot(ax=ax)

# car_sales:> it is dataframe
# "Make" is column, or feature name
# operation is mean
car_sales.groupby(["Make"]).mean()

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