我无法得到熊猫列的平均值或平均值。A有一个数据框架。下面我尝试的两种方法都没有给出列权值的平均值
>>> allDF
ID birthyear weight
0 619040 1962 0.1231231
1 600161 1963 0.981742
2 25602033 1963 1.3123124
3 624870 1987 0.94212
下面返回多个值，而不是一个:
allDF[['weight']].mean(axis=1)
这个也一样:
allDF.groupby('weight').mean()
当前回答
你可以简单地选择: df.describe () 这将为你提供所有你需要的相关细节，但要找到特定列的最小值，最大值或平均值(在你的情况下说“权重”)，使用:
df['weights'].mean(): For average value
df['weights'].max(): For maximum value
df['weights'].min(): For minimum value
其他回答
您可以轻松地执行以下代码
import pandas as pd
import numpy as np
classxii = {'Name':['Karan','Ishan','Aditya','Anant','Ronit'],
'Subject':['Accounts','Economics','Accounts','Economics','Accounts'],
'Score':[87,64,58,74,87],
'Grade':['A1','B2','C1','B1','A2']}
df = pd.DataFrame(classxii,index = ['a','b','c','d','e'],columns=['Name','Subject','Score','Grade'])
print(df)
#use the below for mean if you already have a dataframe
print('mean of score is:')
print(df[['Score']].mean())
你可以使用agg (aggregate)方法:
df.agg('mean')
可以应用多个统计数据:
df.agg(['mean', 'max', 'min'])
此外，如果你想在找到平均值后得到整数。
#Create a DataFrame
df1 = {
'Subject':['semester1','semester2','semester3','semester4','semester1',
'semester2','semester3'],
'Score':[62.73,47.76,55.61,74.67,31.55,77.31,85.47]}
df1 = pd.DataFrame(df1,columns=['Subject','Score'])
rounded_mean = round(df1['Score'].mean()) # specified nothing as decimal place
print(rounded_mean) # 62
rounded_mean_decimal_0 = round(df1['Score'].mean(), 0) # specified decimal place as 0
print(rounded_mean_decimal_0) # 62.0
rounded_mean_decimal_1 = round(df1['Score'].mean(), 1) # specified decimal place as 1
print(rounded_mean_decimal_1) # 62.2
df中每列的平均值:
A B C
0 5 3 8
1 5 3 9
2 8 4 9
df.mean()
A 6.000000
B 3.333333
C 8.666667
dtype: float64
如果你想求所有列的平均值
df.stack().mean()
6.0
如果你只想要权重列的平均值，选择该列(它是一个Series)并调用.mean():
In [479]: df
Out[479]:
ID birthyear weight
0 619040 1962 0.123123
1 600161 1963 0.981742
2 25602033 1963 1.312312
3 624870 1987 0.942120
In [480]: df.loc[:, 'weight'].mean()
Out[480]: 0.83982437500000007
