CODEWITHSUNDEEP
pythonpandasnumpy
Lynn
Lynn

Reputation: 4408

Create threshold and display text if value is above or below a certain value

I have a dataset, df, that contains multiple groups. I would like to set a threshold for each group. If the threshold is above or below a certain value, a certain text should appear.

group      start           end            diff   percent    date

A          2019-04-01      2019-05-01     -160   -11         04-01-2019 to 05-01-2019
A          2019-05-01      2019-06-01     136    8          05-01-2019 to 06-01-2019
B          2020-06-01      2020-07-01     202    5          06-01-2020 to 07-01-2020
B          2020-07-01      2020-08-01     283    7          07-01-2020 to 08-01-2020

I would like to set an upper threshold to any value >250 and a lower threshold to any value <0.

Desired results:

group      start           end            diff   percent    date                        result

A          2019-04-01      2019-05-01     -160   -11        04-01-2019 to 05-01-2019    unacceptable
A          2019-05-01      2019-06-01     136    8          05-01-2019 to 06-01-2019    acceptable
B          2020-06-01      2020-07-01     202    5          06-01-2020 to 07-01-2020    acceptable
B          2020-07-01      2020-08-01     283    7          07-01-2020 to 08-01-2020    unacceptable

This is what I am doing:

df['result'] = df.where(df['percent']> 250,'unacceptable')

This is not working, and I am researching this. Any suggestion is appreciated.

Upvotes: 0

Views: 340

Answers (2)

wwnde
wwnde

Reputation: 26676

Lets try binning

df['result']=pd.cut(df.start, [-np.inf, 0, 250,np.inf], labels=['unacceptablelow','acceptable', 'unacceptablehigh'])


    



        group  start  end        diff percent        date  \
A 2019-04-01  2019-05-01   -160  -11  04-01-2019      to  05-01-2019   
  2019-05-01  2019-06-01    136    8  05-01-2019      to  06-01-2019   
B 2020-06-01  2020-07-01    202    5  06-01-2020      to  07-01-2020   
  2020-07-01  2020-08-01    283    7  07-01-2020      to  08-01-2020   

                        result  
A 2019-04-01   unacceptablelow  
  2019-05-01        acceptable  
B 2020-06-01        acceptable  
  2020-07-01  unacceptablehigh

Upvotes: 1

wasif
wasif

Reputation: 15498

Why not use df.loc instead?

df.loc[df['percent']>250,'percent'] = 'unacceptable'

Upvotes: 1

Related Questions