panda get rows with date range
#greater than the start date and smaller than the end date
mask = (df['date'] > start_date) & (df['date'] <= end_date)
df = df.loc[mask]panda get rows with date range
#greater than the start date and smaller than the end date
mask = (df['date'] > start_date) & (df['date'] <= end_date)
df = df.loc[mask]how to slice dataframe based on daterange in pandas
In [15]: df = pd.DataFrame([1, 2, 3], index=[dt.datetime(2013, 1, 1), dt.datetime(2013, 1, 3), dt.datetime(2013, 1, 5)])
In [16]: df
Out[16]:
0
2013-01-01 1
2013-01-03 2
2013-01-05 3
In [22]: start = df.index.searchsorted(dt.datetime(2013, 1, 2))
In [23]: end = df.index.searchsorted(dt.datetime(2013, 1, 4))
In [24]: df.iloc[start:end]
Out[24]:
0
2013-01-03 2between date pandas
df[df.some_date.between(start_date, end_date)]pandas difference between dates
# credit to Stack Overflow user in the source link
import pandas as pd
# df is your pandas dataframe
# if already datetime64 you don't need to use to_datetime
df['A'] = pd.to_datetime(df['A'])
df['B'] = pd.to_datetime(df['B'])
df['diff'] = df['A'] - df['B'] # difference in daysCopyright © 2021 Codeinu
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