Pandas set_Value with DatetimeIndex [Python]

Question

I'm trying to add the row-wise result from a function into my dataframe using

df.set_Value

.

df

in the format :

    Count   DTW

DateTime        

2015-01-16  10  0

2015-01-17  28  0

Using

df.setValue

dw.set_Value(idx, 'col', dtw) # idx and dtw are int values



TypeError: cannot insert DatetimeIndex with incompatible label

How do I solve this error or what alternative method with comparable efficiency is there?

Answer 1

I think you have Series, not DataFrame, so use Series.set_value with index converted to datetime

dw = pd.Series([-2374], index = [pd.to_datetime('2015-01-18')])
dw.index.name = 'DateTime'
print (dw)
DateTime
2015-01-18   -2374
dtype: int64

print (dw.set_value(pd.to_datetime('2015-01-19'), 1))
DateTime
2015-01-18   -2374
2015-01-19       1
dtype: int64

print (dw.set_value(pd.datetime(2015, 1, 19), 1))
DateTime
2015-01-18   -2374
2015-01-19       1
dtype: int64

More standard way is use ix or iloc:

print (dw)
            Count  DTW
DateTime              
2015-01-16     10    0
2015-01-17     28    0

dw.ix[1, 'DTW'] = 10
#dw.DTW.iloc[1] = 10
print (dw)
            Count  DTW
DateTime              
2015-01-16     10    0
2015-01-17     28   10

Pandas set_Value with DatetimeIndex [Python]

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