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  • Python Pandas -- DataFrame

    pandas.DataFrame

    class pandas.DataFrame(data=Noneindex=Nonecolumns=Nonedtype=Nonecopy=False)[source]

    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

    Column labels to use for resulting frame. Will default to np.arange(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

    See also

    DataFrame.from_records
    constructor from tuples, also record arrays
    DataFrame.from_dict
    from dicts of Series, arrays, or dicts
    DataFrame.from_items
    from sequence of (key, value) pairs

    pandas.read_csvpandas.read_tablepandas.read_clipboard

    1. 先来个小菜

      基于dictionary创建

    from pandas import Series, DataFrame
    import pandas as pd  
    import numpy as np
    d = {'col1':[1,2],'col2':[3,4]}
    df = pd.DataFrame(data=d)
    print(df)
    print(df.dtypes)
    #   col1  col2
    #0     1     3
    #1     2     4
    #col1    int64
    #col2    int64
    #dtype: object

    基于Numy的ndarrary

    df2 = pd.DataFrame(np.random.randint(low=0, high=10, size=(5, 5)),columns=['a', 'b', 'c', 'd', 'e'])
    print (df2)
    #   a  b  c  d  e
    #0  0  2  4  7  0
    #1  6  7  3  4  1
    #2  5  3  3  8  7
    #3  0  9  4  3  4
    #4  7  4  7  0  0
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  • 原文地址:https://www.cnblogs.com/Jesse-Li/p/8808225.html
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