Pandas：在不知道列名的情况下重命名单个 DataFrame 列
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Pandas: Rename single DataFrame column without knowing column name
提问by afrendeiro
I know I can rename single pandas.DataFrame columns with:
我知道我可以重命名单个 pandas.DataFrame 列：
drugInfo.rename(columns = {'col_1': 'col_1_new_name'}, inplace = True)
But I'd like to rename a column without knowing its name (based on its index - although I know dictionaries don't have it). I would like rename column number 1 like this:
但是我想在不知道名称的情况下重命名列（基于其索引 - 尽管我知道字典没有它）。我想像这样重命名第 1 列：
drugInfo.rename(columns = {1: 'col_1_new_name'}, inplace = True)
But in the DataFrame.columns dict there is no '1' entry, so no renaming is done. How could I achieve this?
但是在 DataFrame.columns dict 中没有“1”条目，因此没有重命名。我怎么能做到这一点？
回答by EdChum
Should work:
应该管用：
drugInfo.rename(columns = {list(drugInfo)[1]: 'col_1_new_name'}, inplace = True)
Example:
例子：
In [18]:
df = pd.DataFrame({'a':randn(5), 'b':randn(5), 'c':randn(5)})
df
Out[18]:
a b c
0 -1.429509 -0.652116 0.515545
1 0.563148 -0.536554 -1.316155
2 1.310768 -3.041681 -0.704776
3 -1.403204 1.083727 -0.117787
4 -0.040952 0.108155 -0.092292
In [19]:
df.rename(columns={list(df)[1]:'col1_new_name'}, inplace=True)
df
Out[19]:
a col1_new_name c
0 -1.429509 -0.652116 0.515545
1 0.563148 -0.536554 -1.316155
2 1.310768 -3.041681 -0.704776
3 -1.403204 1.083727 -0.117787
4 -0.040952 0.108155 -0.092292
It is probably more readable to index into the dataframe columns attribute:
索引到数据框列属性可能更具可读性：
df.rename(columns={df.columns[1]:'col1_new_name'}, inplace=True)
So for you:
所以对你来说：
drugInfo.rename(columns = {drugInfo.columns[1]: 'col_1_new_name'}, inplace = True)
