pandas.DataFrame

API
pandas.DataFrame(data=None, index=None, columns=None, dtype=None, copy=False)

具有标记轴(行和列)的二维大小可变、可能异构的表格数据结构。
算术运算在行和列标签上对齐。可以将其视为连续对象的类似于字典的容器。
是主要的panda数据结构。

Parameters:

data : ndarray (structured or homogeneous), Iterable, dict, or DataFrame
Dict can contain Series, arrays, constants, or list-like objects
Changed in version 0.23.0: If data is a dict, column order follows insertion-order for Python 3.6 and later.
Changed in version 0.25.0: If data is a list of dicts, column order follows insertion-order for Python 3.6 and later.

index : Index or array-like
Index to use for resulting frame. Will default to RangeIndex if no indexing information part of input data and no index provided

columns : Index or array-like
Column labels to use for resulting frame. Will default to RangeIndex (0, 1, 2, …, n) if no column labels are provided

dtype : dtype, default None
Data type to force. Only a single dtype is allowed. If None, infer

copy : boolean, default False
Copy data from inputs. Only affects DataFrame / 2d ndarray input

>>> d = {'col1': [1, 2], 'col2': [3, 4]}
>>> df = pd.DataFrame(data=d)
>>> df
   col1  col2
0     1     3
1     2     4

Notice that the inferred dtype is int64.

>>> df.dtypes
col1    int64
col2    int64
dtype: object

To enforce a single dtype:

>>> df = pd.DataFrame(data=d, dtype=np.int8)
>>> df.dtypes
col1    int8
col2    int8
dtype: object

Constructing DataFrame from numpy ndarray:

>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
...                    columns=['a', 'b', 'c'])
>>> df2
   a  b  c
0  1  2  3
1  4  5  6
2  7  8  9