将 pandas DataFrame 的索引增加 1
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Increase index of pandas DataFrame by one
提问by Toby
I'd like to have my dataframe start with index 1 instead of 0. But somehow I am not getting it:
我想让我的数据框以索引 1 而不是 0 开头。但不知何故我没有得到它：
In[1]: df = pd.DataFrame([[4,7],[10,11],[7,2]],columns=['one', 'two'])
In[2]: df
Out[2]:
one two
0 4 7
1 10 11
2 7 2
In[3]: df.reindex(range(1,len(df)+1))
Out[3]:
one two
1 10 11
2 7 2
3 NaN NaN
Where did my first row go? What am I getting wrong about reindex()?
我的第一排去了哪里？我对 reindex() 有什么误解？
回答by EdChum
The reindexing does not reassign the index values and preserve the order for that you can assign directly:
重新索引不会重新分配索引值并保留您可以直接分配的顺序：
In [25]:
df.index = range(1,len(df)+1)
df
Out[25]:
one two
1 4 7
2 10 11
3 7 2
The docsshow that you are conforming your data to the new index which will introduce NaNvalues where none existed hence why you lost a row, this is why there is a fillnaparam for reindex.
该文件表明你符合你的数据，这将引进新的索引NaN，其中没有因此存在，为什么你失去了一排，这就是为什么有一个值fillnaPARAM的reindex。
回答by joctee
To increase your index with 1 you can simply modify the index like this, df.index += 1.
要将索引增加 1，您可以简单地修改索引，df.index += 1.
Full example:
完整示例：
In [1]: import pandas as pd
In [2]: df = pd.DataFrame([[4,7],[10,11],[7,2]],columns=['one', 'two'])
In [3]: df
Out[3]:
one two
0 4 7
1 10 11
2 7 2
In [4]: df.index += 1
In [5]: df
Out[5]:
one two
1 4 7
2 10 11
3 7 2
