[英]Attach index from list to a list of lists to create pandas df
I was wondering if it was possible to create a dataframe from a list of lists, where each item in the index_list is attached as an index to each value in lst:我想知道是否可以从列表列表中创建 dataframe,其中 index_list 中的每个项目都作为索引附加到 lst 中的每个值:
index_list = ['phase1', 'phase2', 'phase3']
lst = [['a', 'b', 'c'], ['d', 'e', 'f', 'g'], ['h', 'i', 'j']]
Thank you for any help!!感谢您的任何帮助!!
Edit: the inner lists are not necessarily the same size.编辑:内部列表的大小不一定相同。
You can use pd.Series.explode
here.您可以在此处使用
pd.Series.explode
。
pd.Series(lst,index=index_list).explode()
phase1 a
phase1 b
phase1 c
phase2 d
phase2 e
phase2 f
phase2 g
phase3 h
phase3 i
phase3 j
dtype: object
Another solution using np.repeat
and np.concatenate
使用
np.repeat
和np.concatenate
另一种解决方案
r_len = [len(r) for r in lst]
pd.Series(np.concatenate(lst), index=np.repeat(index_list,r_len))
phase1 a
phase1 b
phase1 c
phase2 d
phase2 e
phase2 f
phase2 g
phase3 h
phase3 i
phase3 j
dtype: object
Timeit results:时间结果:
In [501]: %%timeit
...: pd.Series(lst,index=index_list).explode()
...:
...:
363 µs ± 16.5 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
In [503]: %%timeit
...: r_len = [len(r) for r in lst]
...: pd.Series(np.concatenate(lst), index=np.repeat(index_list,r_len))
...:
...:
236 µs ± 17.8 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
This problem looks similar to R's expand.grid()
function and is listed in this pandas cookbook (bottom of the page).这个问题看起来类似于 R 的
expand.grid()
function 并列在此pandas 食谱中(页面底部)。 This function lets you to create dataframe with all combinations of the given input values.这个 function 允许您使用给定输入值的所有组合创建 dataframe。
First define a function:首先定义一个function:
def expand_grid(data_dict):
rows = itertools.product(*data_dict.values())
return pd.DataFrame.from_records(rows, columns=data_dict.keys())
Then you can use it like so:然后你可以像这样使用它:
df = expand_grid({'index': ['phase1', 'phase2', 'phase3'],
'Col1': [['a', 'b', 'c'], ['d', 'e', 'f', 'g'], ['h', 'i', 'j']]})
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