CODEWITHSUNDEEP
pythonpandasnumpy
Hamad
Hamad

Reputation: 383

How to create calculation based on conditions using numpy and pandas

I have a column where its categorical (house, neighbors, routine). And I have 4 extra columns. The dataset looks like this:

print(df)

      type    num_before_cleaning      num_after_cleaning    num_before_removing     num_after_removing
0     house          32                       12                    42                      10
1     house          10                       3                     4                       1
2     neighbors      20                       5                     25                      7
3     routine        40                       21                    62                      35 
4     neighbors      14                       2                     21                      9
5     routine        52                       30                    71                      42

and I want for each category in column type it will divide num_before_cleaning / num_after_cleaning and num_before_removing / num_after_removing

So, the outcome will be for example: 

print(house_cleaning)
0.64
print(routine_removing)
0.79

I know that I should use np.where but how can I make it perform calculations after giving it a specific condition? Or is there any other ways I can solve it.

I've tried researching but didn't find any answers.

Upvotes: 0

Views: 72

Answers (1)

jezrael
jezrael

Reputation: 863166

I believe you need:

df1 = df.groupby('type').sum()
df1 = df1.assign(clean = df1.pop('num_before_cleaning').div(df1.pop('num_after_cleaning')),
                 remove = df1.pop('num_before_removing').div(df1.pop('num_after_removing')))
print (df1)
              clean    remove
type                         
house      2.800000  4.181818
neighbors  4.857143  2.875000
routine    1.803922  1.727273

Upvotes: 1

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