熊猫用另一列值替换一列值

Question

这里是示例数据：

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

我愿意用PreviousCandleColor 替换CurrentCandleColor 值，但CurrentCandleColor 的第0 个值应该是PreviousCandleColor 的第一个值。

因此我的最终值必须是：

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

我试着像这样移动它；

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

但我收到以下错误：

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

请帮帮我。

Answer 1

如果这里没有NaNs，则使用shift 和fillna：

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]

或者：

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

如果可能，NaNs 值首先获取列的最后一个值，然后返回：

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