在datafram中减去两列

Question

我的df如下：

Index    Country    Val1  Val2 ... Val10
1        Australia  1     3    ... 5
2        Bambua     12    33   ... 56
3        Tambua     14    34   ... 58

我想从每个国家的Val1中减去Val10，所以输出看起来像：

Country    Val10-Val1
Australia  4
Bambua     23
Tambua     24

到目前为止我有：

def myDelta(row):
    data = row[['Val10', 'Val1']]
    return pd.Series({'Delta': np.subtract(data)})

def runDeltas():
    myDF = getDF() \
        .apply(myDelta, axis=1) \
        .sort_values(by=['Delta'], ascending=False)
    return myDF

runDeltas导致此错误：

ValueError: ('invalid number of arguments', u'occurred at index 9')

解决这个问题的正确方法是什么？

Answer 1

使用此作为df：

df = pd.DataFrame([["Australia", 1, 3, 5],
               ["Bambua", 12, 33, 56],
               ["Tambua", 14, 34, 58]
              ], columns=["Country", "Val1", "Val2", "Val10"]
             )

您还可以做减法运算，并将其放入一个新列中，如下所示。

>>>df['Val_Diff'] = df['Val10'] - df['Val1']

    Country     Val1    Val2  Val10 Val_Diff
0   Australia   1       3      5    4
1   Bambua      12      33     56   44
2   Tambua      14      34     58   44

Answer 2

给定以下数据帧：

df = pd.DataFrame([["Australia", 1, 3, 5],
                   ["Bambua", 12, 33, 56],
                   ["Tambua", 14, 34, 58]
                  ], columns=["Country", "Val1", "Val2", "Val10"]
                 )

它归结为一个简单的broadcasting operation：

>>> val1_minus_val10 = df["Val1"] - df["Val10"]
>>> print(val1_minus_val10)
0    -4
1   -44
2   -44
dtype: int64

Answer 3

您还可以使用pandas.DataFrame.assign函数：例如

import numpy as np
import pandas as pd

df = pd.DataFrame([["Australia", 1, 3, 5],
                   ["Bambua", 12, 33, 56],
                   ["Tambua", 14, 34, 58]
                  ], columns=["Country", "Val1", "Val2", "Val10"]
                 )

df = df.assign(Val10_minus_Val1 = df['Val10'] - df['Val1'])

分配的最佳部分是您可以添加任意数量的分配。e、 g.得到两者的区别，然后记录下来

df = df.assign(Val10_minus_Val1 = df['Val10'] - df['Val1'], log_result = lambda x: np.log(x.Val10_minus_Val1) )

结果：