Python Pandas将零列替换为Nan [英] Python Pandas replace multiple columns zero to Nan
本文介绍了Python Pandas将零列替换为Nan的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
列出了加载到熊猫数据框df2
中的人员的属性的列表.为了进行清理,我想用np.nan
替换零值(0
或'0'
).
List with attributes of persons loaded into pandas dataframe df2
. For cleanup I want to replace value zero (0
or '0'
) by np.nan
.
df2.dtypes
ID object
Name object
Weight float64
Height float64
BootSize object
SuitSize object
Type object
dtype: object
将代码零值设置为np.nan
的工作代码:
Working code to set value zero to np.nan
:
df2.loc[df2['Weight'] == 0,'Weight'] = np.nan
df2.loc[df2['Height'] == 0,'Height'] = np.nan
df2.loc[df2['BootSize'] == '0','BootSize'] = np.nan
df2.loc[df2['SuitSize'] == '0','SuitSize'] = np.nan
可以通过类似/简短的方式来做到这一点:
Believe this can be done in a similar/shorter way:
df2[["Weight","Height","BootSize","SuitSize"]].astype(str).replace('0',np.nan)
但是以上方法不起作用.零保留在df2中.该如何解决?
However the above does not work. The zero's remain in df2. How to tackle this?
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