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参数
keys : 要设置为索引的列名(如有多个应放在一个列表里)drop : 将设置为索引的列删除,默认为Trueappend : 是否将新的索引追加到原索引后(即是否保留原索引),默认为Falseinplace : 是否在原DataFrame上修改,默认为Falseverify_integrity : 是否检查索引有无重复,默认为False
示例
参数keys
keys指定的列将被设置为索引 import pandas as pd data = pd.DataFrame([['Alice', 'Math', 93], ['Bob', 'Physics', 98], ['Chris', 'Chemistry', 96], ['David', 'Biology', 90]], columns=['Name', 'Subject', 'Score']) print(data) print('\n') data1 = data.set_index(keys='Name') print(data1)输出: 将设置为索引的列删除,默认为True import pandas as pd data = pd.DataFrame([['Alice', 'Math', 93], ['Bob', 'Physics', 98], ['Chris', 'Chemistry', 96], ['David', 'Biology', 90]], columns=['Name', 'Subject', 'Score']) print(data) print('\n') data1 = data.set_index(keys='Name') print(data1) print('\n') data2 = data.set_index(keys='Name', drop=False) print(data2)输出: 原索引是否保留。True为保留,默认为False import pandas as pd data = pd.DataFrame([['Alice', 'Math', 93], ['Bob', 'Physics', 98], ['Chris', 'Chemistry', 96], ['David', 'Biology', 90]], columns=['Name', 'Subject', 'Score']) print(data) print('\n') data1 = data.set_index(keys='Name') print(data1) print('\n') data2 = data.set_index(keys='Name', append=True) print(data2)输出: 是否在原DataFrame上修改,默认为False import pandas as pd data = pd.DataFrame([['Alice', 'Math', 93], ['Bob', 'Physics', 98], ['Chris', 'Chemistry', 96], ['David', 'Biology', 90]], columns=['Name', 'Subject', 'Score']) print(data) print('\n') data1 = data.set_index(keys='Name') print(data1) print('\n') data2 = data.set_index(keys='Name', inplace=True) print(data2) print(data)输出: 是否检查索引有无重复,默认为False,若设置为True会影响程序性能,慎用 import pandas as pd data = pd.DataFrame([['Alice', 'Math', 93], ['Bob', 'Physics', 98], ['Chris', 'Chemistry', 96], ['Chris', 'Biology', 90]], columns=['Name', 'Subject', 'Score']) print(data) print('\n') data1 = data.set_index(keys='Name') print(data1) print('\n') data2 = data.set_index(keys='Name', verify_integrity=True) print(data2)输出: 输出: |
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