pandas 熊猫 dropna() 功能不起作用
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Pandas dropna() function not working
提问by Gilgamesh Skytrooper
I am trying to drop NA values from a pandas dataframe.
我正在尝试从 Pandas 数据框中删除 NA 值。
I have used dropna()(which should drop all NA rows from the dataframe). Yet, it does not work.
我已经使用过dropna()（它应该从数据框中删除所有 NA 行）。然而，它不起作用。
Here is the code:
这是代码：
import pandas as pd
import numpy as np
prison_data = pd.read_csv('https://andrewshinsuke.me/docs/compas-scores-two-years.csv')
That's how you get the data frame. As the following shows, the default read_csvmethod does indeed convert the NA data points to np.nan.
这就是您获得数据框的方式。如下所示，默认read_csv方法确实将 NA 数据点转换为np.nan.
np.isnan(prison_data.head()['out_custody'][4])
Out[2]: True
Conveniently, the head()of the DF already contains a NaN values (in the column out_custody), so printing prison_data.head()this, you get:
方便的head()是，DF 的 已经包含一个 NaN 值（在列中out_custody），所以打印prison_data.head()这个，你会得到：
id name first last compas_screening_date sex
0 1 miguel hernandez miguel hernandez 2013-08-14 Male
1 3 kevon dixon kevon dixon 2013-01-27 Male
2 4 ed philo ed philo 2013-04-14 Male
3 5 marcu brown marcu brown 2013-01-13 Male
4 6 bouthy pierrelouis bouthy pierrelouis 2013-03-26 Male
dob age age_cat race ...
0 1947-04-18 69 Greater than 45 Other ...
1 1982-01-22 34 25 - 45 African-American ...
2 1991-05-14 24 Less than 25 African-American ...
3 1993-01-21 23 Less than 25 African-American ...
4 1973-01-22 43 25 - 45 Other ...
v_decile_score v_score_text v_screening_date in_custody out_custody
0 1 Low 2013-08-14 2014-07-07 2014-07-14
1 1 Low 2013-01-27 2013-01-26 2013-02-05
2 3 Low 2013-04-14 2013-06-16 2013-06-16
3 6 Medium 2013-01-13 NaN NaN
4 1 Low 2013-03-26 NaN NaN
priors_count.1 start end event two_year_recid
0 0 0 327 0 0
1 0 9 159 1 1
2 4 0 63 0 1
3 1 0 1174 0 0
4 2 0 1102 0 0
However, running prison_data.dropna()does not change the dataframe in any way.
但是，运行prison_data.dropna()不会以任何方式更改数据帧。
prison_data.dropna()
np.isnan(prison_data.head()['out_custody'][4])
Out[3]: True
回答by rafaelc
df.dropna()by default returns a new dataset without NaNvalues. So, you have to assign it to the variable
df.dropna()默认情况下返回一个没有NaN值的新数据集。所以，你必须将它分配给变量
df = df.dropna()
if you want it to modify the dfinplace, you have to explicitly specify
如果您希望它修改df就地，则必须明确指定
df.dropna(inplace= True)
回答by Gilgamesh Skytrooper
it wasn't working because there was at least one nanper row
它不起作用，因为nan每行至少有一个
