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We will show you how to get the sum of the elements of a Pandas DataFrame column, as well as groupbymethods for calculating cumulative sums and methods for summing columns based on conditions on other column values.

How to get the DataFramesum of a Pandas column

First, we NumPycreate a random array using the library and then use sum()the function to get the sum of each column.

import numpy as np
import pandas as pd

df = pd.DataFrame(np.random.randint(0, 10, size=(10, 4)), columns=list("1234"))
print(df)
Total = df["1"].sum()
print("Column 1 sum:", Total)
Total = df["2"].sum()
print("Column 2 sum:", Total)
Total = df["3"].sum()
print("Column 3 sum:", Total)
Total = df["4"].sum()
print("Column 4 sum:", Total)

If you run this code, you will get the following output (values ​​may be different in your case),

   1  2  3  4
0  2  2  3  8
1  9  4  3  1
2  8  5  6  0
3  9  5  7  4
4  2  7  3  7
5  9  4  1  3
6  6  7  7  3
7  0  4  2  8
8  0  6  6  4
9  5  8  7  2
Column 1 sum: 50
Column 2 sum: 52
Column 3 sum: 45
Column 4 sum: 40

groupbyThe cumulative sum of

We can use groupbythe method to get the cumulative sum. Consider the following with DataFrame, , Fruitand Salecolumns DataFrame:

import pandas as pd

df = pd.DataFrame(
    {
        "Date": ["08/09/2018", "10/09/2018", "08/09/2018", "10/09/2018"],
        "Fruit": ["Apple", "Apple", "Banana", "Banana"],
        "Sale": [34, 12, 22, 27],
    }
)

If we want to calculate the cumulative sales of each fruit, for each date we can calculate it like this,

import pandas as pd

df = pd.DataFrame(
    {
        "Date": ["08/09/2018", "10/09/2018", "08/09/2018", "10/09/2018"],
        "Fruit": ["Apple", "Apple", "Banana", "Banana"],
        "Sale": [34, 12, 22, 27],
    }
)

print(df.groupby(by=["Fruit", "Date"]).sum().groupby(level=[0]).cumsum())

After running the above code, we will get the following output, which shows the cumulative sum of fruits for each date:

Fruit  Date         Sale
Apple  08/09/2018    34
       10/09/2018    46
Banana 08/09/2018    22
       10/09/2018    49
        

How to get the sum of a column based on other column values

This method provides Truethe functionality to get the sum when a given condition is , and Falseto replace the sum with a given value when a condition is . Consider the following code

import numpy as np
import pandas as pd

df = pd.DataFrame(np.random.randn(5, 3), columns=list("xyz"))

df["sum"] = df.loc[df["x"] > 0, ["x", "y"]].sum(axis=1)

df["sum"].fillna(0, inplace=True)
print(df)

In the above code, we add a new column sum DataFrameto , which is ['x'，'y']the sum of the first column , if ['x']is greater than 1, otherwise we replace the sum with 0.

After running the code, we will get the following output (values ​​may change depending on your case).

          x         y         z       sum
0 -1.067619  1.053494  0.179490  0.000000
1 -0.349935  0.531465 -1.350914  0.000000
2 -1.650904  1.534314  1.773287  0.000000
3  2.486195  0.800890 -0.132991  3.287085
4  1.581747 -0.667217 -0.182038  0.914530