Pandas DataFrame 删除某行
Suraj Joshi 2023年1月30日 Pandas Pandas DataFrame Row
本教程说明了如何使用 pandas.DataFrame.drop() 方法在 Pandas 中删除行。
import pandas as pd kgp_df = pd.DataFrame( { "Name": ["Himansh", "Prateek", "Abhishek", "Vidit", "Anupam"], "Age": [30, 33, 35, 30, 30], "Weight(KG)": [75, 75, 80, 70, 73], } ) print("The KGP DataFrame is:") print(kgp_df) 输出：
The KGP DataFrame is: Name Age Weight(KG) 0 Himansh 30 75 1 Prateek 33 75 2 Abhishek 35 80 3 Vidit 30 70 4 Anupam 30 73 我们将使用 kgp_df DataFrame 来解释如何从 Pandas DataFrame 中删除行。
在 pandas.DataFrame.drop() 方法中按索引删除行
import pandas as pd kgp_df = pd.DataFrame( { "Name": ["Himansh", "Prateek", "Abhishek", "Vidit", "Anupam"], "Age": [30, 33, 35, 30, 30], "Weight(KG)": [75, 75, 80, 70, 73], } ) rows_dropped_df = kgp_df.drop(kgp_df.index[[0, 2]]) print("The KGP DataFrame is:") print(kgp_df, "\n") print("The KGP DataFrame after dropping 1st and 3rd DataFrame is:") print(rows_dropped_df) 输出：
The KGP DataFrame is: Name Age Weight(KG) 0 Himansh 30 75 1 Prateek 33 75 2 Abhishek 35 80 3 Vidit 30 70 4 Anupam 30 73 The KGP DataFrame after dropping 1st and 3rd DataFrame is: Name Age Weight(KG) 1 Prateek 33 75 3 Vidit 30 70 4 Anupam 30 73 从 kgp_df DataFrame 中删除索引为 0 和 2 的行。索引 0 和 2 的行对应 DataFrame 中的第一行和第三行，因为索引是从 0 开始的。
我们也可以使用 DataFrame 的索引来删除这些行，而不是使用默认的索引。
import pandas as pd kgp_idx = ["A", "B", "C", "D", "E"] kgp_df = pd.DataFrame( { "Name": ["Himansh", "Prateek", "Abhishek", "Vidit", "Anupam"], "Age": [30, 33, 35, 30, 30], "Weight(KG)": [75, 75, 80, 70, 73], }, index=kgp_idx, ) rows_dropped_df = kgp_df.drop(["A", "C"]) print("The KGP DataFrame is:") print(kgp_df, "\n") print("The KGP DataFrame after dropping 1st and 3rd DataFrame is:") print(rows_dropped_df) 输出：
The KGP DataFrame is: Name Age Weight(KG) A Himansh 30 75 B Prateek 33 75 C Abhishek 35 80 D Vidit 30 70 E Anupam 30 73 The KGP DataFrame after dropping 1st and 3rd DataFrame is: Name Age Weight(KG) B Prateek 33 75 D Vidit 30 70 E Anupam 30 73 它从 DataFrame 中删除索引 A 和 C 的行，或者第一行和第三行。
我们将要删除的行的索引列表传递给 drop() 方法来删除相应的行。
根据 Pandas DataFrame 中某一列的值来删除行
import pandas as pd kgp_idx = ["A", "B", "C", "D", "E"] kgp_df = pd.DataFrame( { "Name": ["Himansh", "Prateek", "Abhishek", "Vidit", "Anupam"], "Age": [31, 33, 35, 36, 34], "Weight(KG)": [75, 75, 80, 70, 73], }, index=kgp_idx, ) young_df_idx = kgp_df[kgp_df["Age"] <= 33].index young_folks = kgp_df.drop(young_df_idx) print("The KGP DataFrame is:") print(kgp_df, "\n") print("The DataFrame of folks with age less than or equal to 33 are:") print(young_folks) 输出：
The KGP DataFrame is: Name Age Weight(KG) A Himansh 31 75 B Prateek 33 75 C Abhishek 35 80 D Vidit 36 70 E Anupam 34 73 The DataFrame of folks with age less than or equal to 33 are: Name Age Weight(KG) C Abhishek 35 80 D Vidit 36 70 E Anupam 34 73 它将删除所有年龄小于或等于 33 岁的行。
我们首先找到所有年龄小于或等于 33 岁的行的索引，然后使用 drop() 方法删除这些行。
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作者： Suraj Joshi
Suraj Joshi is a backend software engineer at Matrice.ai.
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