如何在 Pandas 中的 transpose() 之后删除多余的行（或列）
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How to remove the extra row (or column) after transpose() in Pandas
提问by Helena K
After using transpose on a dataframe there is always an extra row as a remainder from the initial dataframe's index for example:
在数据帧上使用转置后，总会有一个额外的行作为初始数据帧索引的剩余部分，例如：
import pandas as pd
df = pd.DataFrame({'fruit':['apple','banana'],'number':[3,5]})
df
fruit number
0 apple 3
1 banana 5
df.transpose()
0 1
fruit apple banana
number 3 5
Even when i have no index:
即使我没有索引：
df.reset_index(drop = True, inplace = True)
df
fruit number
0 apple 3
1 banana 5
df.transpose()
0 1
fruit apple banana
number 3 5
The problem is that when I save the dataframe to a csv file by:
问题是，当我通过以下方式将数据帧保存到 csv 文件时：
df.to_csv(f)
this extra row stays at the top and I have to remove it manually every time.
这个额外的行保持在顶部，我每次都必须手动删除它。
Also this doesn't work:
这也不起作用：
df.to_csv(f, index = None)
because the old index is no longer considered an index (just another row...).
因为旧索引不再被视为索引（只是另一行......）。
It also happened when I transposed the other way around and I got an extra column which i could not remove.
当我换位时也发生了这种情况，我得到了一个无法删除的额外列。
Any tips?
有小费吗？
回答by user1742571
I had the same problem, I solved it by reseting index before doing the transpose. I mean df.set_index('fruit').transpose():
我遇到了同样的问题，我通过在执行transpose. 我的意思是df.set_index('fruit').transpose()：
import pandas as pd
df = pd.DataFrame({'fruit':['apple','banana'],'number':[3,5]})
df
fruit number
0 apple 3
1 banana 5
And df.set_index('fruit').transpose()gives:
并df.set_index('fruit').transpose()给出：
fruit apple banana
number 3 5
回答by Radhika Nair
Instead of removing the extra index, why don't try setting the new index that you want and then use slicing ?
与其删除额外的索引，不如尝试设置您想要的新索引，然后使用切片？
step 1: Set the new index you want:df.columns = df.iloc[0]
step 2: Create a new dataframe removing extra row.df_new = df[1:]
第 1 步：设置您想要的新索引：df.columns = df.iloc[0]
第 2 步：创建一个新的数据框，删除多余的行。df_new = df[1:]
