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How to select multiple rows of a dataframe by list of dates
dates = pd.date_range('20130101', periods=6)
df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=list('ABCD'))
In[1]: df
Out[1]:
A B C D
2013-01-01 0.084393 -2.460860 -0.118468 0.543618
2013-01-02 -0.024358 -1.012406 -0.222457 1.906462
2013-01-03 -0.305999 -0.858261 0.320587 0.302837
2013-01-04 0.527321 0.425767 -0.994142 0.556027
2013-01-05 0.411410 -1.810460 -1.172034 -1.142847
2013-01-06 -0.969854 0.469045 -0.042532 0.699582
myDates = ["2013-01-02", "2013-01-04", "2013-01-06"]
So the output should be
A B C D
2013-01-02 -0.024358 -1.012406 -0.222457 1.906462
2013-01-04 0.527321 0.425767 -0.994142 0.556027
2013-01-06 -0.969854 0.469045 -0.042532 0.699582
993
In order to select rows between two dates in pandas DataFrame, first, create a boolean mask using mask = (df['InsertedDates'] > start_date) & (df['InsertedDates'] <= end_date) to represent the start and end of the date range. Then you select the DataFrame that lies within the range using the DataFrame. loc[] method.
There are two possible solutions: Use a boolean mask, then use df. loc[mask] Set the date column as a DatetimeIndex, then use df[start_date : end_date]
You can use df[df["Courses"] == 'Spark'] to filter rows by a condition in pandas DataFrame. Not that this expression returns a new DataFrame with selected rows. You can also write the above statement with a variable.
You can use index.isin() method to create a logical index for subsetting:
df[df.index.isin(myDates)]
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