pandas 你如何用标量划分熊猫列？
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How do you divide pandas columns by a scalar?
提问by Nils Wagenaar
I have a file from excel in a pandas dataframe. I have many columns and rows and I want to divide all column and row values (except NaN) by a scalar(2.45). This is what i have:
我在Pandas数据框中有一个来自 excel 的文件。我有很多列和行，我想将所有列和行值（NaN 除外）除以标量（2.45）。这就是我所拥有的：
df = pd.read_excel('Ozflux.dailyLE.xlsx', sheetname='Sheet1', skiprows=0, index_col=2, na_values=[-9999])
ET = df.iloc[4: , 3: ]/2.45
print (ET)
It doesn't give me an error but the values are not divided in ET. Anyone has solution?
它没有给我一个错误，但这些值没有在 ET 中划分。有人有解决方案吗？
回答by Back2Basics
If the whole DataFrame is numerical you can divide all the values (even the NaN's) by 2.45 at once
如果整个 DataFrame 是数字，您可以一次将所有值（甚至是 NaN）除以 2.45
df= df/2.45
print(df)
Notice I had to replace the DataFrame with df =to make it stick.
请注意，我必须用 替换 DataFramedf =以使其保持不变。
