Python Pandas counting and summing specific conditions

Question

Are there single functions in pandas to perform the equivalents of SUMIF  which sums over a specific condition and COUNTIF  which counts values of specific conditions from Excel   I know that there are many multiple step functions that can be used for  for example for sumif I can use  df map lambda x  condition   or df size    then use  sum    and for countif I can use  groupby functions and look for my answer or use a filter and the  count      Is there simple one step process to do these functions where you enter the condition and the data frame and you get the sum or counted results

User · Accepted Answer

You can first make a conditional selection, and sum up the results of the selection using the sum function.

>> df = pd.DataFrame({'a': [1, 2, 3]})
>> df[df.a > 1].sum()   
a    5
dtype: int64

Having more than one condition:

>> df[(df.a > 1) & (df.a < 3)].sum()
a    2
dtype: int64

User · Answer

I usually use numpy sum over the logical condition column    gt  gt  gt  import numpy as np  gt  gt  gt  import pandas as pd  gt  gt  gt  df   pd DataFrame   Age     20 24 18 5 78     gt  gt  gt  np sum df  Age    gt  20  2   This seems to me slightly shorter than the solution presented above

User · Answer

You didn t mention the fancy indexing capabilities of dataframes  e g     gt  gt  gt  df   pd DataFrame   class   1 1 1 2 2    value   1 2 3 4 5     gt  gt  gt  df df  class    1  sum   class    3 value    6 dtype  int64  gt  gt  gt  df df  class    1  sum    value   6  gt  gt  gt  df df  class    1  count    value   3   You could replace df  class    1by another condition

[python] Python Pandas counting and summing specific conditions

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