在本教程中，我们将学习使用pandas 库合并，联接和连接DataFrame 。我认为您已经熟悉数据框和熊猫库。让我们一一看这三个操作。
我们有一个名为pandas.merge()的方法，该方法类似于数据库联接操作 来合并数据帧。请按照以下步骤获得所需的输出。合并 方法将公共列用于合并操作。
初始化数据框。
调用带有三个参数数据帧的方法pandas.merge()，如何（定义数据库联接操作）在（数据帧的公共字段）上。
让我们来看一个例子。
# importing the pandas library
import pandas
# creating dataframes
dataframe_1 = pandas.DataFrame({"Common": ["A", "B", "C", "D", "E"],
"Name": ["John", "Alice", "Emma", "Watson", "Harry"], "Age": [18, 19, 20, 21, 15]}) dataframe_2 = pandas.DataFrame({"Common": ["A", "B", "C", "D", "E"], "Sport": ["Cricket", "Football", "Table Tennis", "Badminton", "Chess"], "Movie": ["Jumanji", "Black Widow", "End Game", "Mr. Robot", "Matrix"]})
# merging using merge method
# how = left or right or inner
new_df = pandas.merge(dataframe_1, dataframe_2, how="left", on="Common") # printing the resultant dataframe print(new_df)输出结果
如果运行上面的代码，您将得到以下结果。
Common Name Age Sport Movie 0 A John 18 Cricket Jumanji 1 B Alice 19 Football Black Widow 2 C Emma 20 Table Tennis End Game 3 D Watson 21 Badminton Mr. Robot 4 E Harry 15 Chess Matrix
与merge方法类似，我们有一个称为dataframe.join(dataframe)的方法用于连接数据框。让我们看看将两个数据框合并为一个的步骤。join方法使用数据帧的索引。
初始化数据帧。
编写一个语句dataframe_1.join（dataframe_2）加入。
让我们尝试一下编码示例。
# importing the pandas library
import pandas
# creating dataframes
dataframe_1 = pandas.DataFrame({"Name": ["John", "Alice", "Emma", "Watson", "Harry"], "Age": [18, 19, 20, 21, 15]}, index = ["A", "B", "C", "D", "E"])dataframe_2 = pandas.DataFrame({"Sport": ["Cricket", "Football", "Table Tennis", "Badminton", "Chess"], "Movie": ["Jumanji", "Black Widow", "End Game", "Mr. Robot", "Matrix"]}, index = ["A", "B", "C", "D", "E"])
# joining
new_df = dataframe_1.join(dataframe_2)
# printing the new dataframe
print(new_df)如果运行上述程序，将得到以下输出
输出结果
Name Age Sport Movie A John 18 Cricket Jumanji B Alice 19 Football Black Widow C Emma 20 Table Tennis End Game D Watson 21 Badminton Mr. Robot E Harry 15 Chess Matrix
与merge和join方法类似，我们有一个称为pandas.concat（list-> dataframes）的方法来连接数据帧。让我们看看连接数据帧的步骤。串联将数据帧合并为一个。
初始化数据帧。
使用pandas.concat（[df_1，df_2，..]）连接数据帧。打印结果。
让我们尝试一下编码示例。
# importing the pandas library
import pandas
# creating dataframes dataframe_1 = pandas.DataFrame({"Name": ["John","Alice","Emma","Watson","Harry"], "Age": [18, 19, 20, 21, 15]}, index = ["A", "B", "C", "D", "E"]) dataframe_2 = pandas.DataFrame({"Name": ["Wick", "Robert", "Elliot", "Baby", "Cruise"], "Age": [22, 20, 45, 15, 42]}, index = ["F", "G", "H", "I", "J"])
# concatenating -> you can pass any number of new_df = pandas.concat([dataframe_1, dataframe_2])
# printing the new dataframe
print(new_df)输出结果
如果运行上述程序，将得到以下输出。
Name Age A John 18 B Alice 19 C Emma 20 D Watson 21 E Harry 15 F Wick 22 G Robert 20 H Elliot 45 I Baby 15 J Cruise 42
如果您对本教程有任何疑问，请在评论部分中提及。