• DataFrame
  • how to create a DataFrame
    • from a source file
  • pd.fillna(method=None,inplace=True)

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import pandas as pd to import pandas library.

DataFrame

一个二维、大小可变的、扁平的表型数据结构；它也有轴线，即行和列，因此可以沿着行和列进行数据运算。 可以认为这是一个类似于字典的序列对象容器。是pandas最主要的数据结构。

DataFrame

see also

• DataFrame.from_records constructor from tuples, also record arrays
• DataFrame.from_dict from dicts of Series, arrays, or dicts
• DataFrame.from_items(http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.from_items.html#pandas.DataFrame.from_items) from sequence of (key, value) pairs
• pandas.read_csv, pandas.read_table, pandas.read_clipboard

how to create a DataFrame

from a source file

• pd.read_csv(filePath)

如果文件以逗号：,进行字段分割，可以直接使用上述代码从源文件中抽取数据构成一个DataFrame对象。

read_csv

**pd.DataFrame()

• 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, otherwise infer

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

• examples

  left = pd.DataFrame({'A': ['A0', 'A1', 'A2'],
                         'B': ['B0', 'B1', 'B2']},
                         index=['K0', 'K1', 'K2'])
  

>>> other = pd.DataFrame({'key': ['K0', 'K1', 'K2'],
                       'B': ['B0', 'B1', 'B2']})
>>> other
    B key
0  B0  K0
1  B1  K1
2  B2  K2

pd.fillna(method=None,inplace=True)

• method=’ffill’

  向前填充空值

• method=’bfill’

  向后填充空值

• inplace=True

  直接修改DataFrame里面的数据，从而影响跟该DataFrame相关的所有的视图等。