Pandas Cookbook

How to do it...

1. Read in the employee dataset, and output the first five rows:

>>> employee = pd.read_csv('data/employee.csv',                            parse_dates=['HIRE_DATE', 'JOB_DATE'])>>> employee.head()

2. Import the seaborn library, and alias it sns:

>>> import seaborn as sns

3. Let's make a bar chart of the count of each department with seaborn:

>>> sns.countplot(y='DEPARTMENT', data=employee)

4. To reproduce this plot with pandas, we will need to aggregate the data beforehand:

>>> employee['DEPARTMENT'].value_counts().plot('barh')

5. Now, let's find the average ...