我有一本具有数千个键的字典,如下所示:
my_dictionary:
{'key1':[['ft1',[2,4,12,2]],['ft2',[0,3,3,1]],'key2':[['ft1',[5,0,2,9]],['ft2',[10,39,3,2]]}
现在,我想将此字典转换为数据框,其中键应为特定列,并且要素(ft1,ft2,..)及其值也将转换为不同的列。所以我想要的数据框应该是这样的:
my_new_dataframe:
ID, ft1_sig,ft1_med,ft1_les,ft1_non,ft2_sig,ft2_med,ft2_les,ft2_non,...
key1 2 4 12 2 0 3 3. 1
key2 5. 0. 2. 9. 10. 39 3. 2
...
keyn. .. .. .. ..
我为此尝试了一种解决方案,但是它要求每个键(即key1,key2等)都包含您要在字典中使用的ft属性。另外,您是否为原始列表缺少“]”?当我粘贴到翻译器中时,它不匹配。
import pandas as pd
#added method to change your original dictionary to one that I can manipulate with the method below.
#If you compare the values of new_dict and data using ==, it returns true.
my_dictionary = {'key1':[['ft1',[2,4,12,2]],['ft2',[0,3,3,1]]],'key2':[['ft1',[5,0,2,9]],['ft2',[10,39,3,2]]]}
new_dict ={}
for element in my_dictionary:
print(element)
print(my_dictionary[element])
new_dict[element] = dict(my_dictionary[element])
print(new_dict)
data = {
'key1':{
'ft1':[2,4,12,2],
'ft2':[0,3,3,1]
},
'key2':{
'ft1':[5,0,2,9],
'ft2':[10,39,3,2]
}
}
keys = list(data.keys())
df = pd.DataFrame.from_dict(data).T
df2 = pd.DataFrame(df.ft1.values.tolist()).add_prefix('ft1_')
df3 = pd.DataFrame(df.ft2.values.tolist()).add_prefix('ft2_')
df4 = pd.merge(df2,df3,left_index=True,right_index=True)
df4.index=keys
print(df4)
这是输出:
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