Pandas 如何合并数据框

要在Pandas中合并数据框，我们将展示一些示例。我们可以轻松地在Pandas中合并数据框甚至是序列。Pandas是一个开源Python库，提供高性能的数据处理和分析工具，使用其强大的数据结构。数据框是一个二维数据结构，即数据以行和列的表格形式对齐。

使用内连接合并数据框

示例

让我们使用Python中的内连接来合并数据框。

import pandas as pd

# Create Dictionaries
dct1 = {'Player':['Jacob','Steve','David','John','Kane'], 'Age':[29, 25, 31, 26, 27]}
dct2 = {'Rank':[1,2,3,4,5], 'Points':[100,87, 80,70, 50]}

# Create DataFrame from Dictionary elements using pandas.dataframe()
df1 = pd.DataFrame(dct1)
df2 = pd.DataFrame(dct2)
print("DataFrame1 = \n",df1)
print("\nDataFrame2 = \n",df2)

# Combining DataFrames using inner join
res = pd.concat([df1, df2], axis=1, join='inner')
print("\nCombined DataFrames = \n",res)

输出

DataFrame1 = 
Player     Age
0  Jacob   29
1  Steve   25
2  David   31
3   John   26
4   Kane   27

DataFrame2 = 
Rank  Points
0     1     100
1     2      87
2     3      80
3     4      70
4     5      50
Combined DataFrames = 
Player     Age  Rank  Points
0  Jacob   29     1     100
1  Steve   25     2      87
2  David   31     3      80
3   John   26     4      70
4   Kane   27     5      50

使用append()合并DataFrame

示例

在这个示例中，我们将使用Python的append()函数合并数据框

import pandas as pd

# Create Dictionaries
dct1 = {'Player':['Steve','David'], 'Age':[29, 25,]}
dct2 = {'Player':['John','Kane'], 'Age':[31, 27]}

# Create DataFrame from Dictionary elements using pandas.dataframe()
df1 = pd.DataFrame(dct1)
df2 = pd.DataFrame(dct2)
print("DataFrame1 = \n",df1)
print("\nDataFrame2 = \n",df2)

# Combining DataFrames using append()
res = df1.append(df2)
print("\nCombined DataFrames = \n",res)

输出

DataFrame1 = 
Player     Age
0  Steve   29
1  David   25

DataFrame2 = 
   Player  Age
0   John   31
1   Kane   27

Combined DataFrames = 
Player     Age
0  Steve   29
1  David   25
0   John   31
1   Kane   27

使用concat()函数合并DataFrame

示例

在这个示例中，我们将使用Python中的concat()函数来合并数据框。

import pandas as pd

# Create Dictionaries
dct1 = {'Player':['Steve','David'], 'Age':[29, 25,]}
dct2 = {'Player':['John','Kane'], 'Age':[31, 27]}

# Create DataFrame from Dictionary elements using pandas.dataframe()
df1 = pd.DataFrame(dct1)
df2 = pd.DataFrame(dct2)
print("DataFrame1 = \n",df1)
print("\nDataFrame2 = \n",df2)

# Combining DataFrames using concat()
res = pd.concat([df1, df2])
print("\nCombined DataFrames = \n",res)

输出

DataFrame1 = 
Player     Age
0  Steve   29
1  David   25DataFrame2 = 
Player     Age
0   John   31
1   Kane   27
Combined DataFrames = 
Player     Age
0  Steve   29
1  David   25
0   John   31
1   Kane   27