How can pandas resample a daily time series to a monthly time series and retrieve the first available value of each month?

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To resample a daily time series to a monthly time series and retrieve the first available value of each month, you can use the pandas resample() function along with the agg() function to apply the first() method to each group of monthly values:

import pandas as pd

# Create a sample daily time series
dates = pd.date_range(start='2021-01-01', end='2021-12-31', freq='D')
values = range(365)
df = pd.DataFrame({'date': dates, 'value': values})
df.set_index('date', inplace=True)

# Resample to monthly and retrieve first value
monthly = df.resample('M').agg({'value': 'first'})

In this example, the resample() function is called with the argument 'M', which indicates that we want to resample the time series to months. The agg() function is then called with a dictionary that specifies the column to aggregate ('value') and the method to use ('first').