如何使用 pandas 从 DataFrame 中的所有元素中减去一个数字?

How to subtract a number from all elements in a DataFrame with pandas?

我正在尝试使用 pandas 从 DataFrame 中的所有元素中减去一个数字。但是,只有第一个元素被减去,其他元素得到 NaN.

这是数据: DataFrame_3x5.csv

A   B   C
0.1 0.3 0.5
0.2 0.4 0.6
0.3 0.5 0.7
0.4 0.6 0.8
0.5 0.7 0.9

这是我的代码:

import pandas as pd
data = pd.read_csv(r"DataFrame_3x5.csv")
df = pd.DataFrame(data)
medianList = pd.DataFrame()

for i in range(0, data.shape[1]):
  medianList = medianList.append([df.iloc[:,i].median()], ignore_index=True)

for i in range(0, data.shape[1]):
  print(data.iloc[:,i])
  print(medianList.iloc[i])
  print(data.iloc[:,i] - medianList.iloc[i])
  # print(data.iloc[:,i].sub([medianList.iloc[i]], axis='columns')) # doesn't work

结果如下:

0    0.1
1    0.2
2    0.3
3    0.4
4    0.5
Name: A, dtype: float64
0    0.3
Name: 0, dtype: float64
0   -0.2
1    NaN
2    NaN
3    NaN
4    NaN
dtype: float64
0    0.3
1    0.4
2    0.5
3    0.6
4    0.7
Name: B, dtype: float64
0    0.5
Name: 1, dtype: float64
0   -0.2
1    NaN
2    NaN
3    NaN
4    NaN
dtype: float64
0    0.5
1    0.6
2    0.7
3    0.8
4    0.9
Name: C, dtype: float64
0    0.7
Name: 2, dtype: float64
0   -0.2
1    NaN
2    NaN
3    NaN
4    NaN
dtype: float64

我的期望:

0   -0.2
1   -0.1
2    0.0
3    0.1
4    0.2

根据this site,

print(data.iloc[:,i].sub([medianList.iloc[i]], axis='columns'))

... 应该可以,但实际上会产生错误:

ValueError: No axis named columns for object type <class 'pandas.core.series.Series'>

我不知道该怎么办了。请帮我。谢谢。

我想如果你先尝试 dropna 然后简单地减去它就可以了

df=df.dropna(how='any')
df['Sub']=int(df['A']) - int(df['B']) - int(df['C'])

你可以这样做:

df - df.median(axis=0)

和 pandas 会处理用于计算值的轴

一个简单的解决方案:

import pandas as pd
df = pd.read_csv(r"DataFrame_3x5.csv")

df['A'] - df['A'].median()

import pandas as pd
data = pd.read_csv(r"DataFrame_3x5.csv")
df = pd.DataFrame(data)
medianList = pd.DataFrame()
for i in range(0, data.shape[1]):
  medianList = medianList.append([df.iloc[:,i].median()], ignore_index=True)

df1 = pd.DataFrame(columns=['A'])
j=0
for i in range(0, data.shape[0]):
    print(data['A'].iloc[i]) # one column
    print(medianList.iloc[i])  #1 value
    print(data['A'].iloc[i] - medianList.iloc[j])