这是我的数据帧。如何我添加MAX_VALUE,MIN_VALUE,mean_value,中值名行让我的索引值会是怎样
0
1
2
3
4
MAX_VALUE
MIN_VALUE
平均值
中值
谁能帮我解决这个
如果要添加行使用添加DataFrame.agg
:
df1 = df.append(df.agg(['max','min','mean','median']))
如果要添加列使用assign
与min
,max
,mean
和median
:
df2 = df.assign(max_value=df.max(axis=1),
min_value=df.min(axis=1),
mean_value=df.mean(axis=1),
median_value=df.median(axis=1))
一种方法是,
由于@jezrael的帮助。
df = pd.DataFrame(np.random.randint(0,100,size=(5, 4)), columns=list('ABCD'))
df1=df.copy()
#column wise calc
df.loc['max']=df1.max()
df.loc['min']=df1.min()
df.loc['mean']=df1.mean()
df.loc['median']=df1.median()
#row wise calc
df['max']=df1.max(axis=1)
df['min']=df1.min(axis=1)
df['mean']=df1.mean(axis=1)
df['median']=df1.median(axis=1)
O / P:
A B C D max min mean median
0 49.0 91.0 16.0 17.0 91.0 16.0 43.25 33.0
1 20.0 42.0 86.0 60.0 86.0 20.0 52.00 51.0
2 32.0 25.0 94.0 13.0 94.0 13.0 41.00 28.5
3 40.0 1.0 66.0 31.0 66.0 1.0 34.50 35.5
4 18.0 30.0 67.0 31.0 67.0 18.0 36.50 30.5
max 49.0 91.0 94.0 60.0 NaN NaN NaN NaN
min 18.0 1.0 16.0 13.0 NaN NaN NaN NaN
mean 31.8 37.8 65.8 30.4 NaN NaN NaN NaN
median 32.0 30.0 67.0 31.0 NaN NaN NaN NaN
这种运作良好,罚款:
df1 = df.copy()
df.loc['max']=df1.max()
df.loc['min']=df1.min()
df.loc['mean']=df1.mean()
df.loc['median']=df1.median()