CODEWITHSUNDEEP
python-3.xpandaspython-3.5
Jaffer Wilson
Jaffer Wilson

Reputation: 7273

Pandas replacing the one column value with other

Here is the sample data: 

Time,RangeGreen,RangeRed,DistanceGreenRed,SlopeGreen,SlopeRed,PreviousCandleColor,CurrentCandleColor
2018.04.02 00:01:01,30-40,20-30,14.42241040084485,0.002837507264410963,-0.002233901393132696,Green,indecisive
2018.04.02 00:03:06,40-50,30-40,9.228956001044772,3.969502900848433,7.203315124348411,Green,indecisive
2018.04.02 00:04:06,10-20,30-40,-13.69498672180752,-19.36590965829607,-2.850639197642629,Red,indecisive

I am willing to replace the CurrentCandleColor values with the PreviousCandleColor but the 0th value of CurrentCandleColor should be the 1st value of PreviousCandleColor.

Hence my final value must be: 

Time,RangeGreen,RangeRed,DistanceGreenRed,SlopeGreen,SlopeRed,PreviousCandleColor,CurrentCandleColor
2018.04.02 00:01:01,30-40,20-30,14.42241040084485,0.002837507264410963,-0.002233901393132696,Green,Green
2018.04.02 00:03:06,40-50,30-40,9.228956001044772,3.969502900848433,7.203315124348411,Green,Red
2018.04.02 00:04:06,10-20,30-40,-13.69498672180752,-19.36590965829607,-2.850639197642629,Red,indecisive

I tried to move it somewhat like this; 

df['CurrentCandleColor'] = df[1:'PreviousCandleColor']

But I got the following error: 

TypeError: cannot do slice indexing on <class 'pandas.core.indexes.range.RangeIndex'> with these indexers [PreviousCandleColor] of <class 'str'>

Kindly, help me.

Upvotes: 1

Views: 32

Answers (1)

jezrael
jezrael

Reputation: 863166

Use shift with fillna if no NaNs here:

a = df.loc[df.index[-1], 'CurrentCandleColor']
df['CurrentCandleColor'] = df['PreviousCandleColor'].shift(-1).fillna(a)
print (df)
                  Time        ...         CurrentCandleColor
0  2018.04.02 00:01:01        ...                      Green
1  2018.04.02 00:03:06        ...                        Red
2  2018.04.02 00:04:06        ...                 indecisive

[3 rows x 8 columns]

Or:

df['CurrentCandleColor'] =df['PreviousCandleColor'].shift(-1).fillna(df['CurrentCandleColor'])

If possible NaNs values first get last value of column and then set back:

last = df['CurrentCandleColor'].values[-1]
df['CurrentCandleColor'] = df['PreviousCandleColor'].shift(-1)
df.loc[df.index[-1], 'CurrentCandleColor'] = last

Upvotes: 1

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