[英]Merge two pandas dataframes, as lists in every cell
I want to merge 2 dataframes, with the resulting dataframe having a list in every single cell.我想合并 2 个数据框,生成的数据框在每个单元格中都有一个列表。 I'm completely lost on how to do this.
我完全不知道如何做到这一点。
My current solution is using the index of each dataframe to build a dict (eg. dict[index[0]]['DEPTH'] = []
), and then looping over rows of the dataframes to append to dict keys (eg. dict[index[0]]['DEPTH'].append(cell_value)
), but I'm thinking that's super inefficient and slow.我当前的解决方案是使用每个数据帧的索引来构建一个字典(例如
dict[index[0]]['DEPTH'] = []
),然后循环遍历数据帧的行以附加到字典键(例如。 dict[index[0]]['DEPTH'].append(cell_value)
),但我认为这是超级低效和缓慢的。
Does a pandas solution exist that would get this done?是否存在可以完成此任务的 pandas 解决方案?
DEPTH A
chr1~10007022~C [1, 1] [0, 0]
chr1~10007023~T [1, 1] [0, 0]
.
.
.
chr1~10076693~T [1, 1] [0, 0]
Keep in mind:记住:
You could concatenate the two, groupby the item and then agg with list.您可以将两者连接起来,按项目分组,然后用列表聚合。
import pandas as pd
df = pd.DataFrame({'item':['chr1-10007022-C', 'chr1-10007023-T'],
'DEPTH':[1,1],
'A':[0,0],
'C':[0,0]})
df = df.set_index('item')
df2 = pd.DataFrame({'item':['chr1-10007022-C', 'chr1-10007026-X'],
'DEPTH':[1,1],
'A':[0,0],
'C':[0,0]})
df2 = df2.set_index('item')
out = pd.concat([df,df2]).groupby(level=0).agg(list)
Output输出
DEPTH A C
item
chr1-10007022-C [1, 1] [0, 0] [0, 0]
chr1-10007023-T [1] [0] [0]
chr1-10007026-X [1] [0] [0]
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