我有一个csv文件。我读了:

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?

最佳答案

使用带有参数dropna subset 来指定检查NaN的列:

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

boolean indexing notnull 的另一种解决方案:
data = data[data['sms'].notnull()]
print (data)
   id city department   sms  category
1   2  lhr    revenue  good         1

query 替代:
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

08-28 13:04