使用
dropna带有参数
subset的指定检查列
NaNS：
data = data.dropna(subset=['sms'])print (data) id city department sms category1 2 lhr revenue good 1
用另一种解决方案
boolean indexing和
notnull：
data = data[data['sms'].notnull()]print (data) id city department sms category1 2 lhr revenue good 1
另一种选择
query：
print (data.query("sms == sms")) id city department sms category1 2 lhr revenue good 1时机
#[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 loopIn [124]: %timeit (data[data['sms'].notnull()])100 loops, best of 3: 13.8 ms per loopIn [125]: %timeit (data.query("sms == sms"))10 loops, best of 3: 23.6 ms per loop
