Python, Pandas to add columns from calculation

Question

A data frame like this and I am adding some columns from mapping and calculation.

   code month of entry   name  reports
0    JJ       20171002  Jason       14
1    MM       20171206  Molly       24
2    TT       20171208   Tina       31
3    JJ       20171018   Jake       22
4    AA       20090506    Amy       34
5    DD       20171128  Daisy       16
6    RR       20101216  River       47
7    KK       20171230   Kate       32
8    DD       20171115  David       14
9    JJ       20171030   Jack       10
10   NN       20171216  Nancy       28

What it is doing here is select some rows and look up the values from the dictionary and insert a further column from simple calculation. It works fine:

import pandas as pd

data = {'name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy', 'Daisy', 'River', 'Kate', 'David', 'Jack', 'Nancy'], 
    'code' : ['JJ', 'MM', 'TT', 'JJ', 'AA', 'DD', 'RR', 'KK', 'DD', 'JJ', 'NN'],
    'month of entry': ["20171002", "20171206", "20171208", "20171018", "20090506", "20171128", "20101216", "20171230", "20171115", "20171030", "20171216"],
    'reports': [14, 24, 31, 22, 34, 16, 47, 32, 14, 10, 28]}
df = pd.DataFrame(data)

dict_hour = {'JasonJJ' : 3, 'MollyMM' : 6, 'TinaTT' : 2, 'JakeJJ' : 3, 'AmyAA' : 8, 'DaisyDD' : 6, 'RiverRR' : 4, 'KateKK' : 8, 'DavidDD' : 5, 'JackJJ' : 5, 'NancyNN' : 2}

wanted = ['JasonJJ', 'TinaTT', 'AmyAA', 'DaisyDD', 'KateKK']

df['name_code'] = df['name'].astype(str) + df['code'].astype(str)

df1 = df[df['name_code'].isin(wanted)]

df1['hour'] = df1['name_code'].map(dict_hour).astype(float)

df1['coefficient'] = df1['reports'] / df1['hour'] - 1

But the last 2 lines received a same warning:

SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

How can the code can be improved accordingly? Thank you.

jezrael · Accepted Answer · 2018-03-16 09:09:57Z

3

You need copy:

df1 = df[df['name_code'].isin(wanted)].copy()

If you modify values in df1 later you will find that the modifications do not propagate back to the original data (df), and that Pandas does warning.

edited Mar 16, 2018 at 9:09

answered Mar 16, 2018 at 9:08

jezrael

868k103 gold badges1.4k silver badges1.3k bronze badges

Sign up to request clarification or add additional context in comments.

1 Comment

Mark K Over a year ago

too fast too furious your response! :)

Collectives™ on Stack Overflow

Python, Pandas to add columns from calculation

1 Answer 1

1 Comment

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

1 Comment

Your Answer

Sign up or log in

Post as a guest

Linked

Related