Sheet

How can I find the average age for each row in this example. Each columns has its own age ranging from 0 to 90. I have read the csv with pandas.

CodePudding user response：

Assuming the values are the amount of people per age, here is one solution.

(Potentially not the fastest for large amount of data)

highest_age = 90

def row_age(x):
    sum_age = 0
    sum_people = 0
    for i in range(0, highest_age   1):
        people = x[f"age_{i}"]
        sum_people  = people
        sum_age  = people * i
    if sum_people > 0:
        return sum_age / sum_people


df["average_age"] = df.apply(row_age, axis=1)

CodePudding user response：

I Assume all the age-related columns are named like Age_0, Age_1, Age_2, ...

import pandas as pd
import numpy as np

df = pd.read_csv("./data.csv")

ages = np.array([int(c.split("_")[-1]) for c in df.filter(regex="^Age_\d $").columns])
df.loc[:, "avg_age"] = (df.filter(regex="^Age_\d $").values * ages).sum(axis=1) / df.filter(regex="^Age_\d $").values.sum(axis=1)