divide alternating rows in table in python

You can divide alternating rows in a table by using pandas library in Python. Here's an example code:

main.py
import pandas as pd

# create sample dataset
data = {'employee_id': [101, 102, 103, 104, 105, 106],
        'employee_name': ['Alice', 'Bob', 'Charlie', 'David', 'Eva', 'Frank'],
        'department': ['Sales', 'Marketing', 'Sales', 'Human Resource', 'Marketing', 'Human Resource']}
df = pd.DataFrame(data)

# divide alternating rows using loc attribute and boolean indexing
df.loc[::2, 'employee_id':'department'] = df.loc[::2, 'employee_id':'department'].apply(lambda x: x.str.upper())

# display updated dataset
print(df)
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In this code, we use the loc attribute to select every other row, starting from the first row (i.e., ::2). We then specify the columns we want to update (i.e., employee_id to department) using slicing. Finally, we use the apply() method with a lambda function to uppercase the values in the selected rows.

Note that this code assumes that the table has a header row, and that the first row is at index 0. Also, you can modify the column names and the condition for selecting rows depending on your specific use case.