如何在 Pandas 中找到两行之间的差异？

在本文中，我们将了解如何在 Pandas 中找到两行之间的差异。

Pandas DataFrame 是一种带有标记轴的表格形式的二维数据结构。在数据分析期间，可能需要计算两行之间的差异以进行比较。这可以使用pandas.DataFrame.diff()函数来完成。此函数计算两个连续 DataFrame 元素之间的差异。

Syntax: pandas.DataFrame.diff(periods=1, axis=0)

Parameters:

• periods: Represents periods to shift for computing difference, Integer type value. Default value is 1
• axis: Represents difference to be taken over rown or columns. Can take two values {0: rows, 1: columns}. Default value is 0

Returns: Returns DataFrame

示例 1：为了测试这个函数，我们创建了一个 3 列 6 行的虚拟 DataFrame。现在，这个 diff函数将找出每一行与其前一行的差异，默认情况下，周期为 1。因此，第 0 个索引行中的值是 NaN。

Python3

# Importing Pandas Library
import pandas as pd 
  
# Creating dummy DataFrame for testing
df = pd.DataFrame({ 'a': [1, 2, 3, 4, 5, 6],
                    'b': [8, 18, 27, 20, 33, 49],
                    'c': [2, 24, 6, 16, 20, 52]})
# Printing DataFrame before applying diff function
print(df)
  
# Printing DataFrame after applying diff function
print("Difference: ")
print(df.diff())

输出：

a   b   c
0  1   8   2
1  2  18  24
2  3  27   6
3  4  20  16
4  5  33  20
5  6  49  52
Difference: 
     a     b     c
0  NaN   NaN   NaN
1  1.0  10.0  22.0
2  1.0   9.0 -18.0
3  1.0  -7.0  10.0
4  1.0  13.0   4.0
5  1.0  16.0  32.0

示例 2：

Python3

# Importing Pandas Library
import pandas as pd 
  
# Creating dummy DataFrame for testing
df = pd.DataFrame({ 'a': [1, 2, 3, 4, 5, 6],
                    'b': [8, 18, 27, 20, 33, 49],
                    'c': [2, 24, 6, 16, 20, 52]})
# Printing DataFrame before applying diff function
print(df)
  
# Printing DataFrame after applying diff function
print("Difference: ")
print(df.diff(periods=2))

输出：

a   b   c
0  1   8   2
1  2  18  24
2  3  27   6
3  4  20  16
4  5  33  20
5  6  49  52
Difference: 
     a     b     c
0  NaN   NaN   NaN
1  NaN   NaN   NaN
2  2.0  19.0   4.0
3  2.0   2.0  -8.0
4  2.0   6.0  14.0
5  2.0  29.0  36.0