Python 如果 Pandas 数据框中的特定列中存在空值，则删除行
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Delete rows if there are null values in a specific column in Pandas dataframe
提问by kumar
Am new to python pandas. Need some help with deleting few rows where there are null values. In the screenshot, I need to delete rows where charge_per_line = - using python pandas. Thanks !!
我是 python 熊猫的新手。需要一些帮助来删除有空值的几行。在屏幕截图中，我需要使用 python pandas 删除 charge_per_line = - 的行。谢谢 ！！
回答by jpp
If the relevant entries in Charge_Per_Line are empty (NaN) when you read into pandas, you can use df.dropna:
如果NaN读入pandas时Charge_Per_Line中的相关条目为空( )，则可以使用df.dropna：
df = df.dropna(axis=0, subset=['Charge_Per_Line'])
If the values are genuinely -, then you can replace them with np.nanand then use df.dropna:
如果这些值是真的-，那么您可以将它们替换为np.nan，然后使用df.dropna：
import numpy as np
df['Charge_Per_Line'] = df['Charge_Per_Line'].replace('-', np.nan)
df = df.dropna(axis=0, subset=['Charge_Per_Line'])
回答by Vaishali
Multiple ways
多种方式
Use str.contains to find rows containing '-'
df[~df['Charge_Per_Line'].str.contains('-')]Replace '-' by nan and use dropna()
df.replace('-', np.nan, inplace = True) df = df.dropna()
使用 str.contains 查找包含“-”的行
df[~df['Charge_Per_Line'].str.contains('-')]用 nan 替换 '-' 并使用 dropna()
df.replace('-', np.nan, inplace = True) df = df.dropna()
