python - Pandas dataframe: how to create columns from values? -

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i have pandas dataframe looks like:

            day payment_method  actuals    0   2015-03-31      dcash_t3m       32          1   2015-03-31   dcash_t3m_3d       90          2   2015-03-31         paypal       34          4   2015-04-01      dcash_t3m       16         5   2015-04-01   dcash_t3m_3d       54         6   2015-04-01         paypal       33          7   2015-04-02      dcash_t3m        7         8   2015-04-02   dcash_t3m_3d       80         9   2015-04-02         paypal       38

what want perform time series analysis on them. advantageous if had column each payment method reporting corresponding actuals , order total values , times series.

       day dcash_t3m dcash_t3m_3d paypal 2015-03-31        32          90      34 2015-04-01        16          54      33 2015-04-02         7          80      38

datatime object new column distinct date each roe. values of column payment_method 3 new columns each of them containing values in actuals.

you want pivot:

in [27]: df.pivot(index='day', columns = 'payment_method', values = 'actuals')  out[27]: payment_method  dcash_t3m  dcash_t3m_3d  paypal day                                             2015-03-31             32            90      34 2015-04-01             16            54      33 2015-04-02              7            80      38

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