根据条件对df进行分段显示jupyter中的nan值
[英]Segmenting a df based on condition shows nan values in jupyter
问题描述
Using df[columns][df[colums]<0.5] to segment a DataFrame in Pandas usually only showed me the rows matching this condition. 
使用df[columns][df[colums]<0.5]分割Pandas中的DataFrame通常只向我显示匹配此条件的行。
Just recently I end up getting NaN - Values shown: 就在最近，我最终得到NaN-显示的值：
Was there an update I'm missing or what is causing this behaviour usually? 我是否缺少更新，或者通常是什么导致此行为？
Dropping all NaN with .dropna() is obviously a fast solution to this issue, but doesn't explain the change in "behaviour". 使用.dropna()删除所有NaN显然是解决此问题的快速方法，但没有解释“行为”的更改。
Fix: Don't put columns in double brackets.. 修正：不要将列放在双括号中。
1 个解决方案
解决方案1
2 已采纳 2019-05-28 12:33:22
如果需要按一列进行比较并按多列进行过滤，请使用带有boolean indexing DataFrame.loc ：
df.loc[df['district-heating'] < 0.5, ['id','district-heating']]
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