将包含嵌套列表列表的字典转换为 df
convert dictionary containing nested list of lists to df
我有一本字典,其中包含我认为称为列表嵌套列表的内容,如下所示....
data = {'length': [[1633345896441, 101.25], [1633348822964, 101.67], [1633353200096, 102.32]], 'weight' : [[1633345896441, 7.09], [1633348822964, 7.44], [1633353200096, 7.51]]}
我正在尝试转换为单个 df,如下所示....
date length weight
0 1633345896441 101.25 7.09
1 1633348822964 101.67 7.44
2 1633353200096 102.32 7.51
然而,到目前为止,我的努力似乎走错了方向......
k, v = list(data.items())[0]
df = pd.DataFrame(v).reset_index(drop=True)
急需帮助 - 请
一种方法:
import pandas as pd
data = {'length': [[1633345896441, 101.25], [1633348822964, 101.67], [1633353200096, 102.32]],
'weight' : [[1633345896441, 7.09], [1633348822964, 7.44], [1633353200096, 7.51]]}
df = pd.DataFrame({k : dict(v) for k, v in data.items()}).rename_axis("date").reset_index()
print(df)
输出
date length weight
0 1633345896441 101.25 7.09
1 1633348822964 101.67 7.44
2 1633353200096 102.32 7.51
我有一本字典,其中包含我认为称为列表嵌套列表的内容,如下所示....
data = {'length': [[1633345896441, 101.25], [1633348822964, 101.67], [1633353200096, 102.32]], 'weight' : [[1633345896441, 7.09], [1633348822964, 7.44], [1633353200096, 7.51]]}
我正在尝试转换为单个 df,如下所示....
date length weight
0 1633345896441 101.25 7.09
1 1633348822964 101.67 7.44
2 1633353200096 102.32 7.51
然而,到目前为止,我的努力似乎走错了方向......
k, v = list(data.items())[0]
df = pd.DataFrame(v).reset_index(drop=True)
急需帮助 - 请
一种方法:
import pandas as pd
data = {'length': [[1633345896441, 101.25], [1633348822964, 101.67], [1633353200096, 102.32]],
'weight' : [[1633345896441, 7.09], [1633348822964, 7.44], [1633353200096, 7.51]]}
df = pd.DataFrame({k : dict(v) for k, v in data.items()}).rename_axis("date").reset_index()
print(df)
输出
date length weight
0 1633345896441 101.25 7.09
1 1633348822964 101.67 7.44
2 1633353200096 102.32 7.51