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DataFrame.transpose函数
transpose()函数有助于转置数据帧的索引和列。通过将行写为列，反之亦然。
语法
DataFrame.transpose(*args, **kwargs)
返回值
它返回转置的DataFrame。
例1
# importing pandas as pd import pandas as pd # 创建数据框 info = pd.DataFrame({'Weight':[27, 44, 38, 10, 67], 'Name':['William', 'John', 'Learnfk', 'Parker', 'Jones'], 'Age':[22, 17, 19, 24, 27]}) # 创建索引 index_ = pd.date_range('2010-10-04 06:15', periods = 5, freq ='H') # 设置索引 info.index = index_ # 打印数据框 print(info) # 数据转置 result = info.transpose() # 打印结果 print(result)
输出
Weight Name Age
2010-10-04 06:15:00 27 William 22
2010-10-04 07:15:00 44 John 7
2010-10-04 08:15:00 38 Learnfk 19
2010-10-04 09:15:00 10 Parker 24
2010-10-04 10:15:00 67 Jones 27
2010-10-04 06:15:00 2010-10-04 07:15:00 2010-10-04 08:15:00 \
Weight 27 44 38
Name William John Learnfk
Age 22 7 19
2010-10-04 09:15:00 2010-10-04 10:15:00
Weight 10 67
Name Parker Jones
Age 24 27
例2
# importing pandas as pd import pandas as pd # 创建数据框 info = pd.DataFrame({"A":[8, 2, 7, None, 6], "B":[4, 3, None, 9, 2], "C":[17, 42, 35, 18, 24], "D":[15, 18, None, 11, 12]}) # 创建索引 index_ = ['Row1', 'Row2', 'Row3', 'Row4', 'Row5'] # 设置索引 info.index = index_ # 打印数据框 print(info) # 返回转置 result = info.transpose() # 打印结果 print(result)
输出
A B C D
Row_1 8.0 4.0 17 15.0
Row_2 2.0 3.0 42 18.0
Row_3 7.0 NaN 35 NaN
Row_4 NaN 9.0 18 11.0
Row_5 6.0 2.0 24 12.0
Row1 Row2 Row3 Row4 Row5
A 8.0 2.0 7.0 NaN 6.0
B 4.0 3.0 NaN 9.0 2.0
C 17.0 42.0 35.0 18.0 24.0
D 15.0 18.0 NaN 11.0 12.0
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