如何复制 Pandas DataFrame 中的行并添加 id 列
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How do I copy rows in a pandas DataFrame and add an id column
提问by Racing Tadpole
I have a dataframe such as:
我有一个数据框，例如：
from pandas import DataFrame
import pandas as pd
x = DataFrame.from_dict({'farm' : ['A','B','A','B'],
'fruit':['apple','apple','pear','pear']})
How can I copy it Ntimes with an id, eg. to output (for N=2):
我怎样才能N用一个 id复制它，例如。输出（用于N=2）：
farm fruit sim
0 A apple 0
1 B apple 0
2 A pear 0
3 B pear 0
0 A apple 1
1 B apple 1
2 A pear 1
3 B pear 1
I tried an approach which works on dataframes in R:
我尝试了一种适用于 R 中数据帧的方法：
from numpy import arange
N = 2
sim_ids = DataFrame(arange(N))
pd.merge(left=x, right=sim_ids, how='left')
but this fails with the error MergeError: No common columns to perform merge on.
但这因错误而失败MergeError: No common columns to perform merge on。
Thanks.
谢谢。
回答by Phillip Cloud
Not sure what R is doing there, but here's a way to do what you want:
不确定 R 在那里做什么，但这里有一种方法可以做你想做的事：
In [150]: x
Out[150]:
farm fruit
0 A apple
1 B apple
2 A pear
3 B pear
[4 rows x 2 columns]
In [151]: N = 2
In [152]: DataFrame(tile(x, (N, 1)), columns=x.columns).join(DataFrame({'sims': repeat(arange(N), len(x))}))
Out[152]:
farm fruit sims
0 A apple 0
1 B apple 0
2 A pear 0
3 B pear 0
4 A apple 1
5 B apple 1
6 A pear 1
7 B pear 1
[8 rows x 3 columns]
In [153]: N = 3
In [154]: DataFrame(tile(x, (N, 1)), columns=x.columns).join(DataFrame({'sims': repeat(arange(N), len(x))}))
Out[154]:
farm fruit sims
0 A apple 0
1 B apple 0
2 A pear 0
3 B pear 0
4 A apple 1
5 B apple 1
6 A pear 1
7 B pear 1
8 A apple 2
9 B apple 2
10 A pear 2
11 B pear 2
[12 rows x 3 columns]
回答by DSM
I might do something like:
我可能会做这样的事情：
>>> df_new = pd.concat([df]*2)
>>> df_new["id"] = df_new.groupby(level=0).cumcount()
>>> df_new
farm fruit id
0 A apple 0
1 B apple 0
2 A pear 0
3 B pear 0
0 A apple 1
1 B apple 1
2 A pear 1
3 B pear 1
[8 rows x 3 columns]
