Python：如何删除特定列为空/ NaN的行？

我有一个csv文件.我读了它：

import pandas as pd
data = pd.read_csv('my_data.csv', sep=',')
data.head()

它的输出如下：

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.什么是有效的方法呢？

解决方法:

将dropna与参数子集一起使用以指定用于检查NaN的列：

data = data.dropna(subset=['sms'])
print (data)
   id city department   sms  category
1   2  lhr    revenue  good         1

boolean indexing和notnull的另一个解决方案：

data = data[data['sms'].notnull()]
print (data)
   id city department   sms  category
1   2  lhr    revenue  good         1

替代query：

print (data.query("sms == sms"))
   id city department   sms  category
1   2  lhr    revenue  good         1

计时

#[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