3 views
in Python

I have 2 columns:

X Y

1 3

1 4

2 6

1 6

2 3

How to sum up values of Y where X=1 e.g this will give me [3+4+6=13] in pandas?

by (10.9k points)
edited

@Alex , you may refer to the following approaches:

1.Using groupby() which splits the dataframe into parts according to the value in column ‘X’ -

df.groupby('X')['Y'].sum()[1]

13

2.Similarly, we can use Boolean indexing where loc is used to handle indexing of rows and columns-

df.loc[df['X'] == 1, 'Y'].sum()

13

3.Query can also be used in order to filter rows you are interested in-

df.query("X == 1")['Y'].sum()

13

Similarly, if you had three columns :

Ex-

X Y  Z
1 3   2

1 4   2

2 6   2

1 6   2

2  3  2

And you want to sum the rows of Y where Z is 2 and X is 2 ,then we may use the following:

1.groupby()

df.groupby('X')['Y'].sum()

2.Query

df.query("X == 2 and Z == 2")['Y'].sum()

3.Boolean indexing

df.loc[(df['X'] == 2) & (df['Z'] == 2), 'Y'].sum()

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by (106k points)

You can also do this without using groupby or loc. By simply including the condition in code. Let the name of dataframe be df. Then you can try :

df[df['a']==1]['b'].sum()

or you can also try :

sum(df[df['a']==1]['b'])

Another way could be to use the numpy library of python :

import numpy as np

print(np.where(df['a']==1, df['b'],0).sum())

You can use the following video tutorials to clear all your doubts:-

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