Python Pandas -- DataFrame

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pandas.DataFrame

class  pandas. DataFrame( data=None,  index=None,  columns=None,  dtype=None,  copy=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_csv, pandas.read_table, pandas.read_clipboard

1. 先來個小菜

  基於dictionary建立

from pandas import Series, DataFrameimport pandas as pd  import numpy as npd = {‘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

基於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

 

Python Pandas -- DataFrame