Python Pandas - 过滤无值
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Pandas - Filtering None Values
提问by Shadin
I'm using Pandas to explore some datasets. I have this dataframe:
我正在使用 Pandas 来探索一些数据集。我有这个数据框：
I want to exclude any row that has a city value. So I've tried:
我想排除任何具有城市值的行。所以我试过：
new_df = all_df[(all_df["City"] == "None") ]
new_df
But then I got an empty dataframe:
但是后来我得到了一个空的数据框：
It works whenever I use any value other than None. Any idea how to filter this dataframe?
每当我使用除None. 知道如何过滤这个数据框吗？
采纳答案by tarashypka
Consider using isnull()to locate missing values
考虑使用isnull()定位缺失值
all_df[all_df['City'].isnull()]
回答by Bodhi94
I hope "where" can do what you expect
我希望“ where”能做到你所期望的
new_df = new_df.where(new_df["city"], None)
And it is better use np.nanrather than None.
它更好地使用np.nan而不是None.
For more details pandas.DataFrame.where
有关更多详细信息pandas.DataFrame.where
回答by imanzabet
Try this to select only the Nonevalues for city column:
试试这个只选择None城市列的值：
new_df = all_df['City'][all_df['City'] == "None"]
Try this to see all other columns which has the same rows of 'City'==None
试试这个以查看具有相同行的所有其他列 'City'==None
new_df = all_df[all_df['City'] == "None"]
print(new_df.head()) # with function head() you can see the first 5 rows
