[FIXED] How to plot a Horizontal bar with y-axis value from categorical data

Issue

The organization is the index and I need to show a horizontal bar plot showing the total number of attempts of experiments conducted by each organization, with the most at the top and the fewest at the bottom.

The data frame are as follows : Organization DateTime Attempts a .... Failed b .... Success b .... Failed a .... Partial Success a .... Success b .... Partial Success

I got the idea that the attempts is categorical data and it has some count_values() function but just don't know how to code it?

Solution

Let's assume this input:

np.random.seed(0)
df = pd.DataFrame({'company': np.random.choice(['A', 'B', 'C', 'D'], 50),
                   'Location': 'non-relevant',
                   'Outcome': np.random.choice(['Success', 'Failure'], 50),
                  }).set_index('company')
df.head()

             Location  Outcome
company                       
A        non-relevant  Success
D        non-relevant  Failure
B        non-relevant  Failure
A        non-relevant  Failure
D        non-relevant  Failure
...

Calculate the counts per group and sort:

>>> df2 = df.groupby('company')['Outcome'].count().sort_values()
>>> df2
company
C     8
A    12
B    12
D    18
Name: Outcome, dtype: int64

plot:

df2.plot.barh()

And here how to calculate with failure/successes:

df2 = df.groupby('company')['Outcome'].value_counts().unstack('Outcome')
df2 = df2.loc[df2.sum(axis=1).sort_values().index]
df2.plot.barh(stacked='True')

Answered By - mozway