如何在 pandas 中获取使用另一列的值选择的行的平均值 [英] How to get mean of rows selected with another column's values in pandas

问题描述

仅当列Dates等于Oct-16时，我才试图计算得分1的平均值:

I am trying to get calculate the mean for Score 1 only if column Dates is equal to Oct-16:

我最初尝试的是:

 import pandas as pd
 import numpy as np
 import os

 dataFrame = pd.read_csv("test.csv")

 for date in dataFrame["Dates"]:
    if date == "Oct-16":
        print(date)##Just checking
        print(dataFrame["Score 1"].mean())

但是我的结果是整列Score 1

我尝试的另一件事是手动告诉它要计算哪些指数的平均值:

Another thing I tried was manually telling it which indices to calculate the mean for:

dataFrame["Score 1"].iloc[0:2].mean()

但是理想情况下，如果Dates == "Oct-16"，我想找到一种方法.

But ideally I would like to find a way to do it if Dates == "Oct-16".

推荐答案

遍历行并没有利用Pandas的优势.如果要基于另一列的值对某列进行操作，则可以使用

Iterating through the rows doesn't take advantage of Pandas' strengths. If you want to do something with a column based on values of another column, you can use .loc[]:

dataFrame.loc[dataFrame['Dates'] == 'Oct-16', 'Score 1']

.loc[]的第一部分使用指定的条件(dataFrame['Dates'] == 'Oct-16')选择所需的行.第二部分指定所需的列(Score 1).然后，如果您想获取均值，则可以在末尾放置.mean():

The first part of .loc[] selects the rows you want, using your specified criteria (dataFrame['Dates'] == 'Oct-16'). The second part specifies the column you want (Score 1). Then if you want to get the mean, you can just put .mean() on the end:

dataFrame.loc[dataFrame['Dates'] == 'Oct-16', 'Score 1'].mean()

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