Slicing by dates in Python is a common task when working with time series data. Here's an example of how to slice a pandas DataFrame by date range:

import pandas as pd
 
# Create a sample DataFrame
df = pd.DataFrame({
    'date': pd.date_range('2022-01-01', '2022-01-10'),
    'value': range(10)
})
 
# Set the date column as the index
df = df.set_index('date')
 
# Slice the DataFrame by date range
start_date = '2022-01-03'
end_date = '2022-01-07'
sliced_df = df.loc[start_date:end_date]
 
# Print the sliced DataFrame
print(sliced_df)

In this example, we create a sample DataFrame with a date column and a value column. We then set the date column as the index using the set_index method. We can then slice the DataFrame by specifying a start date and an end date using the loc method. Finally, we print the sliced DataFrame to the console.

This will output the following:

value
date
2022-01-03      2
2022-01-04      3
2022-01-05      4
2022-01-06      5
2022-01-07      6

 

This shows us that the DataFrame has been sliced to include only rows with dates between start_date and end_date.