问题描述
我的数据帧为400 x25.我应该从数据集中删除所有Nan，然后从25列中只选择要处理的3列.我使用以下方法完成此操作:
i have a dataframe of 400 x 25. i am supposed to remove ALL Nans from the dataset and then select only 3 columns to work on from the 25 columns. I have done this using:
df1.dropna(axis=0)
df2=df1.loc[:,['bgr','wc','rc']]
df2['rc']=pd.to_numeric(df['rc'],errors='coerce')
df2['wc']=pd.to_numeric(df['wc'],errors='coerce')
当我执行dtypes时，rc和wc显示为对象，所以我将它们转换为浮点数.
rc and wc were showing up as objects when i did the dtypes, so i converted them to floats.
现在，在放下Nans之后，我只剩下252行.所以我以为所有的Nans都走了.
now, after i drop the Nans, i am left with only 252 rows. so i assumed that all the Nans had gone.
但是当我执行df2.describe()时，它显示rc为251，而bgr和wc为252.这很奇怪，所以当我执行df2.rc.unique()时，它显示了Nan ！！！
but when i did a df2.describe(), it showed 251 as count for 'rc' but 252 for 'bgr' and 'wc'. this was odd, so when i did a df2.rc.unique(), it showed up a Nan!!!!
我的问题:如何删除这个Nan?
my question: how do i remove this Nan??
推荐答案
重新分配:
df = df.dropna(axis=0)
默认情况下，它不是就位的，除非您这样说:
by default it's not inplace unless you say so:
df.dropna(axis=0, inplace=True)
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