DataFrame.from_records

DataFrame.from_records(data, index=None, exclude=None, columns=None, coerce_float=False, nrows=None)
从结构化的ndarray、元组或字典序列创建一个DataFrame对象。

Parameters

data	结构化的ndarray、元组或字典序列的输入数据
index	用作索引的数组字段，或者使用一组特定的输入标签
exclude	要排除的列或字段
columns	要使用的列名
coerce_float	尝试将非字符串、非数字对象（如Decimal）的值转换为浮点数
nrows	如果数据是迭代器，读取的行数

Example：data

query_set = Entry.objects.all()
df = pd.DataFrame.from_records(query_set.values())

Example：data

import pandas as pd
data = [{"name": "google", "age": 18}, {"name": "baidu", "age": 20}]
pd.DataFrame.from_records(data)
---------------------------------------------------------
    name    age
0    google    18
1    baidu    20

Example：index

import pandas as pd
data = [{"name": "google", "age": 18}, {"name": "baidu", "age": 20}]
pd.DataFrame.from_records(data, index=["first", "second"])
---------------------------------------------------------
        name    age
first    google    18
second    baidu    20

Example：exclude

import pandas as pd
data = [{"name": "google", "age": 18}, {"name": "baidu", "age": 20}]
pd.DataFrame.from_records(data, exclude=["age"])
---------------------------------------------------
    name
0    google
1    baidu

Example：columns

import pandas as pd
data = [("google", 18), ("baidu", 20), ("apple", 30)]
pd.DataFrame.from_records(data, columns=["site", "age"])
------------------------------------------------------
    site    age
0    google    18
1    baidu    20
2    apple    30