Python:如何删除特定列为空/NaN的行? [英] Python: How to drop a row whose particular column is empty/NaN?
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问题描述
我有一个csv文件.我读了:
I have a csv file. I read it:
import pandas as pd
data = pd.read_csv('my_data.csv', sep=',')
data.head()
其输出如下:
id city department sms category
01 khi revenue NaN 0
02 lhr revenue good 1
03 lhr revenue NaN 0
我想删除sms
列为空/NaN的所有行.什么是有效的方法?
I want to remove all the rows where sms
column is empty/NaN. What is efficient way to do it?
推荐答案
使用 dropna
,带有参数subset
用于指定检查NaN
s的列:
Use dropna
with parameter subset
for specify column for check NaN
s:
data = data.dropna(subset=['sms'])
print (data)
id city department sms category
1 2 lhr revenue good 1
使用 boolean indexing
和 notnull
:
data = data[data['sms'].notnull()]
print (data)
id city department sms category
1 2 lhr revenue good 1
使用 query
替代:
Alternative with query
:
print (data.query("sms == sms"))
id city department sms category
1 2 lhr revenue good 1
时间
#[300000 rows x 5 columns]
data = pd.concat([data]*100000).reset_index(drop=True)
In [123]: %timeit (data.dropna(subset=['sms']))
100 loops, best of 3: 19.5 ms per loop
In [124]: %timeit (data[data['sms'].notnull()])
100 loops, best of 3: 13.8 ms per loop
In [125]: %timeit (data.query("sms == sms"))
10 loops, best of 3: 23.6 ms per loop
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