Adding rows in pandas with repeated index

Question

So far, when I needed to add rows to a dataframe, I used loc (or more rarely, iloc). In a dataframe like this one:

                         key1           key2        value
  2014-02-03 12:00:00     22             32         98.89
  2014-02-03 12:00:00     23             33         99.25
  2014-02-03 12:00:00     24             34         99.78
  2014-02-03 15:00:00     22             32         96.54
  2014-02-03 15:00:00     23             33         97.21
  2014-02-03 15:00:00     24             34         98.59

I used:

df.loc[pd.to_datetime('2014-02-03 18:00:00')] = [23, 32, 98.84]

But if I need to add rows with the same index (imagine another row with 2014-02-03 15:00:00) then loc gives me error. I have been trying methods like concat or merge but I don't get anything. Thanks.

jezrael · Accepted Answer · 2017-06-13 12:38:19Z

1

For me works concat with another DataFrame:

df.loc[pd.to_datetime('2014-02-03 18:00:00')] = [23, 32, 98.84]
df1 = pd.DataFrame([[23, 32, 100]], 
                    columns=df.columns, 
                    index=[pd.to_datetime('2014-02-03 15:00:00')])
print (df1)
                     key1  key2  value
2014-02-03 15:00:00    23    32    100

df = pd.concat([df, df1])
print (df)
                    key1  key2   value
2014-02-03 12:00:00   22  32.0   98.89
2014-02-03 12:00:00   23  33.0   99.25
2014-02-03 12:00:00   24  34.0   99.78
2014-02-03 15:00:00   22  32.0   96.54
2014-02-03 15:00:00   23  33.0   97.21
2014-02-03 15:00:00   24  34.0   98.59
2014-02-03 18:00:00   23  32.0   98.84
2014-02-03 15:00:00   23  32.0  100.00

answered Jun 13, 2017 at 12:38

jezrael

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2 Comments

David Over a year ago

Hello again :-). Yes, concat works. I was getting in bad order the columns when creating a new dataframe, so that was my problem. But with your df.columns it works. Thanks.

jezrael Over a year ago

Glad can help. ;)

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