向现有数据框添加新行

Question

这是我的数据框。如何在行中添加max_value，min_value，mean_value，median_value名称，以使索引值类似于

0

1

2

3

4

max_value

min_value

均值

median_value

谁能帮助我解决这个问题

Answer 1

如果要添加行，请使用添加DataFrame.agg：

df1 = df.append(df.agg(['max','min','mean','median']))

如果要添加列，请将assign与min，max，mean和median一起使用：

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))

Answer 2

一种方法，

感谢@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

Answer 3

这很好并且很好：

df1 = df.copy()
df.loc['max']=df1.max()
df.loc['min']=df1.min()
df.loc['mean']=df1.mean()
df.loc['median']=df1.median()