Inserting row in pandas dataframe based on date using datetime index

Question

               col_A    vi_B    data_source index_as_date
2017-01-21  0.000000  0.199354         sat       2017-01-21
2017-01-22  0.000000  0.204250         NaN           NaT
2017-01-23  0.000000  0.208077         NaN           NaT
2017-01-27  0.000000  0.215081         NaN           NaT
2017-01-28  0.000000  0.215300         NaN           NaT

In the pandas dataframe above, I want to insert a row for 24th January 2017 with value of 0.01, 0.4, sat, NaT, how do I do that? I could use iloc and manually insert but I would prefer an automated solution which takes the datetime index into account

jezrael · Accepted Answer · 2017-10-12 05:10:25Z

2

I think you need setting with enlargement with sort_index:

#if necessary convert to datetime
df.index = pd.to_datetime(df.index)
df['index_as_date'] = pd.to_datetime(df['index_as_date'])

df.loc[pd.to_datetime('2017-01-24')] = [0.01,0.4,'sat', pd.NaT]
df = df.sort_index()
print (df)

            col_A      vi_B data_source index_as_date
2017-01-21   0.00  0.199354         sat    2017-01-21
2017-01-22   0.00  0.204250         NaN           NaT
2017-01-23   0.00  0.208077         NaN           NaT
2017-01-24   0.01  0.400000         sat           NaT
2017-01-27   0.00  0.215081         NaN           NaT
2017-01-28   0.00  0.215300         NaN           NaT

edited Oct 12, 2017 at 5:10

answered Oct 12, 2017 at 5:05

jezrael

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