pandas.DataFrame.__init__¶
- DataFrame.__init__(data=None, index=None, columns=None, dtype=None, copy=False)¶
Two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. Can be thought of as a dict-like container for Series objects. The primary pandas data structure
Parameters : data : numpy ndarray (structured or homogeneous), dict, or DataFrame
Dict can contain Series, arrays, constants, or list-like objects
index : Index or array-like
Index to use for resulting frame. Will default to np.arange(n) if no indexing information part of input data and no index provided
columns : Index or array-like
Will default to np.arange(n) if not column labels provided
dtype : dtype, default None
Data type to force, otherwise infer
copy : boolean, default False
Copy data from inputs. Only affects DataFrame / 2d ndarray input
See also
- DataFrame.from_records
- constructor from tuples, also record arrays
- DataFrame.from_dict
- from dicts of Series, arrays, or dicts
- DataFrame.from_csv
- from CSV files
- DataFrame.from_items
- from sequence of (key, value) pairs
read_csv
Examples
>>> d = {'col1': ts1, 'col2': ts2} >>> df = DataFrame(data=d, index=index) >>> df2 = DataFrame(np.random.randn(10, 5)) >>> df3 = DataFrame(np.random.randn(10, 5), ... columns=['a', 'b', 'c', 'd', 'e'])