[英]Python Pandas: Convert nested dictionary to dataframe
I have a dic like this:我有一个这样的 dic:
{1 : {'tp': 26, 'fp': 112},
2 : {'tp': 26, 'fp': 91},
3 : {'tp': 23, 'fp': 74}}
and I would like to convert in into a dataframe like this:我想转换成这样的数据帧:
t tp fp
1 26 112
2 26 91
3 23 74
Does anybody know how?有人知道怎么做吗?
Try DataFrame.from_dict()
and with keyword argument orient
as 'index'
-尝试
DataFrame.from_dict()
并使用关键字参数orient
作为'index'
-
Example -例子 -
In [20]: d = {1 : {'tp': 26, 'fp': 112},
....: 2 : {'tp': 26, 'fp': 91},
....: 3 : {'tp': 23, 'fp': 74}}
In [24]: df =pd.DataFrame.from_dict(d,orient='index')
In [25]: df
Out[25]:
tp fp
1 26 112
2 26 91
3 23 74
If you also want to set the column name for index
column , use - df.index.name
, Example -如果您还想为
index
列设置列名,请使用df.index.name
,示例 -
In [30]: df.index.name = 't'
In [31]: df
Out[31]:
tp fp
t
1 26 112
2 26 91
3 23 74
I just wanted to note (as this is one of the top results for converting from a nested dictionary to a pandas dataframe) that there are other ways of nesting dictionaries that can be also be converted to a dataframe (eg nesting via columns).我只是想指出(因为这是从嵌套字典转换为 Pandas 数据帧的最佳结果之一)还有其他嵌套字典的方法也可以转换为数据帧(例如通过列嵌套)。
eg the following nested dictionary例如下面的嵌套字典
patients = {"Name":{"0":"John","1":"Nick","2":"Ali","3":"Joseph"},
"Gender":{"0":"Male","1":"Male","2":"Female","3":"Male"},
"Nationality":{"0":"UK","1":"French","2":"USA","3":"Brazil"},
"Age" :{"0":10,"1":25,"2":35,"3":29}}
can be converted to a pandas dataframe using orient='columns'可以使用 orient='columns' 转换为 Pandas 数据框
df_patients = pd.DataFrame.from_dict(patients, orient='columns')
另一个简单的方法是
df =pd.DataFrame(dict).T
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