Panda dataframe column conditional on another column - 


import pandas pd import urllib.request import numpy np url="https://www.misoenergy.org/library/repository/market%20reports/20170811_da_bc.xls"  cnstxls = urllib.request.urlopen(url) xl = pd.excelfile(cnstxls) df = xl.parse("sheet1",skiprows=3) constr = df.iloc[:,1:7] constr['class'] = np.where(constr['hour of occurrence'] == (1,2,3,4,5,6), 'offpeak', 'onpeak') sumsp=constr.groupby('constraint_id','class',axis=0)['shadow price'].sum().sort_values(ascending=true)`

1) new column class giving errors - says typeerror: invalid type comparison. how set new column based on multiple hours? works when put 1 hour (1 or 2 or 3...)

2) typeerror: groupby() got multiple values argument 'axis'. groupby using 2 columns. works 1 column.

let's try:

constr['class'] = np.where(constr['hour of occurrence'].isin([1,2,3,4,5,6]),'offpeak','onpeak')  sumsp = constr.groupby(['constraint_id','class'],axis=0)['shadow price'].sum().sort_values(ascending=true)  print(sumsp)

output:

constraint_id  class   281292         onpeak    -780.05 1049           onpeak    -364.68 4636           onpeak    -276.62 201082         onpeak    -245.44 1607           onpeak    -237.36 98333          onpeak    -112.05 107318         onpeak     -96.10 270366         onpeak     -80.71 267644         onpeak     -73.25 285770         onpeak     -59.53 1049           offpeak    -46.52 281292         offpeak    -33.80 270888         onpeak     -19.68 289484         offpeak    -10.41                onpeak      -4.52 1607           offpeak     -2.60 9712           onpeak       0.84 268470         onpeak       1.14 248010         onpeak       1.48 287090         onpeak       1.63                offpeak     11.78 188144         offpeak     26.32 4862           onpeak      28.03 285770         offpeak     50.21 name: shadow price, dtype: float64

edit unstack pivot class:

sumsp.unstack('class')

output:

class          offpeak  onpeak constraint_id                  1049            -46.52 -364.68 1607             -2.60 -237.36 4636               nan -276.62 4862               nan   28.03 9712               nan    0.84 98333              nan -112.05 107318             nan  -96.10 188144           26.32     nan 201082             nan -245.44 248010             nan    1.48 267644             nan  -73.25 268470             nan    1.14 270366             nan  -80.71 270888             nan  -19.68 281292          -33.80 -780.05 285770           50.21  -59.53 287090           11.78    1.63 289484          -10.41   -4.52

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