如何有效地解压缩这种类型的结构并创建数据帧?

Question

同时使用

import networkx as nx
nx.fruchterman_reingold_layout()

我只剩下这种类型的数据结构：

{'SomeKey': array([value1,  value2]),
'SomeOtherKey': array([value1, value2])}

我已经尝试过以下代码：

empty_dataframe = pd.DataFrame(columns=["Person", "x", "y"])
list_of_keys = list(fruchterman.keys())
for key in list_of_keys:
dataframe = pd.DataFrame({"Person": key, "x": [fruchterman[key][0]], "y": [fruchterman[key][1]]})
for_later_save.append(dataframe, ignore_index=True)

我要么收到一个错误，说我为标量值或空数据帧提供了错误的索引：

Empty DataFrame
Columns: [Person, x, y]
Index: []

尝试不同的方法也是无效的：

Exception has occurred: IndexError
invalid index to scalar variable.
File "Y:Directory1Directory2Directory3calculations.py", line 75, in <module>
dataframe = pd.DataFrame({"Person": key, "x": [fruchterman[key][0][0]], "y": [fruchterman[key][0][1]]})

Answer 1

给定您的数据：

• pd.DataFrame.from_dict应该努力解开data

数据：

data = {'SomeKey': array(['value1',  'value2']),
'SomeOtherKey': array(['value1', 'value2'])}

orient='columns'：

df = pd.DataFrame.from_dict(data, orient='columns')
print(df)
SomeKey SomeOtherKey
0  value1       value1
1  value2       value2

orient='index'：

df = pd.DataFrame.from_dict(data, orient='index')
df.reset_index(inplace=True)
df.columns = ['Person', 'x', 'y']
print(df)
Person       x       y
0       SomeKey  value1  value2
1  SomeOtherKey  value1  value2