如何有效地解壓縮這種類型的結構並創建一個DataFrame？

Question

在使用生成x和y坐標時

import networkx as nx
nx.fruchterman_reingold_layout()

我剩下這種類型的數據結構：

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

我已經嘗試過以下代碼：

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)

我收到一個錯誤，說我為標量值或空的DataFrame提供了錯誤的索引：

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

嘗試不同的方法也是無效的：

Exception has occurred: IndexError
invalid index to scalar variable.
  File "Y:\Directory1\Directory2\Directory3\calculations.py", line 75, in <module>
    dataframe = pd.DataFrame({"Person": key, "x": [fruchterman[key][0][0]], "y": [fruchterman[key][0][1]]})

Answer 1

根據您的數據：

• pd.DataFrame.from_dict應該可以解壓縮data

數據：

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