如何在 pandas df中设置新索引并删除默认索引 [英] How to set new index and remove default index in pandas df

问题描述

我已经在图片中附加了数据框. 在df中，subVoyageID是默认索引，我试图删除subvoyageID旁边的空白行，以便所有列名都在同一行中对齐，但是我无法做到这一点.

I have attached the dataframe in the pic. In the df, subVoyageID is the default index, I am trying to remove that blank row next to the subvoyageID, so that all the column names are aligned in the same row, but I am unable to do it.

由于subVoyageID是默认索引，因此我将数据复制到了新列"svid"中，并将索引重置为新列"svid"，(请参见下面的代码和图片)

Since subVoyageID is the default index, I copied the data into new col "svid" and reset the index to new column "svid", (see the code and pic below)

    df["SVID"] = df.index
    df.set_index('SVID')
    df

原始df

结果df

现在我该如何摆脱第一列即默认索引，因为df.info()显示了从x-max到SVID的5列；还是有其他方法可以将所有列标签对齐在一行中.感谢您的帮助.

Now how do I get rid of the very first column which was the default index, as df.info() shows 5 columns from x-max to SVID; Or is there any other way I could align all the column labels in one row. Thanks for any help.

推荐答案

使用 reset_index 用于将索引值转换为列，并在必要时将rename列转换为

df = df.reset_index().rename(columns={'subVoyageID':'SVID'})

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