python基礎(chǔ)數(shù)據(jù)分析--pandas（一）

2019-11-06 08:06:36

字體：大中小

供稿：網(wǎng)友

本文為原創(chuàng)，未經(jīng)允許，不得轉(zhuǎn)載。

1、pandas的數(shù)據(jù)結(jié)構(gòu)

1）Series：是一種類似于一維數(shù)組的對象，它由一組數(shù)據(jù)（各種NumPy數(shù)據(jù)類型）以及一組與之相關(guān)的數(shù)據(jù)標(biāo)簽（即索引）組成。它可以看做一個定長的有序字典。基本任意的一維數(shù)據(jù)都可以用來構(gòu)造 Series 對象。

2）DataFrame：是一個表格型的數(shù)據(jù)結(jié)構(gòu)，它含有一組有序的列，每列可以是不同的值類型（數(shù)值、字符串、布爾值的）。DataFrame既有行索引也有列索引，它可以被看做由Series組成的字典。

Series 和 DataFrame 分別對應(yīng)于numpy一維的序列和二維的表結(jié)構(gòu)。

2. pandas的數(shù)據(jù)結(jié)構(gòu)DataFrame是一個表格型的數(shù)據(jù)結(jié)構(gòu)，它含有一組有序的列，每列可以是不同的值類型（數(shù)值、字符串、布爾值的）。

下面具體練習(xí)：

import pandas as pd

import numpy as np

#Series 對象包含兩個主要的屬性：index 和 values

w =pd.Series(data=[1,3,5,7],index = ['a','b','c','d'])

PRint (w)a    1b    3
c    5
d    7
dtype: int64
w.index
Index(['a', 'b', 'c', 'd'], dtype='object')w.values
array([1, 3, 5, 7], dtype=int64)s = pd.Series([1,3,5,np.nan,6,8])
print(s)
0    1.01    3.0
2    5.0
3    NaN
4    6.0
5    8.0
dtype: float64
##非常常用的函數(shù)date_range，尤其是在處理時間序列數(shù)據(jù)時，這個函數(shù)的作用就是產(chǎn)生一個##DatetimeIndex，就是時間序列數(shù)據(jù)的索引
dates = pd.date_range('20130101', periods=6) 
# periods：表示你要從這個函數(shù)產(chǎn)生多少個日期索引值
dates 
DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04','2013-01-05', '2013-01-06'],
dtype='datetime64[ns]', freq='D')
df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=list('ABCD'))
print(df)
  A B C D
2013-01-01 -0.747037 -0.665933 0.506150 -0.047263
2013-01-02 -0.501075 0.843647 0.506725 -0.499766
2013-01-03 -1.171445 0.816434 0.761552 -0.908022
2013-01-04 -0.226046 -0.472765 3.075716 1.063544
2013-01-05 0.108281 -0.122184 -0.011140 -1.287596
2013-01-06 -1.499848 -0.430267 2.074067 -1.067155
df1 = pd.DataFrame(np.random.randn(6,4), index=['a','b','c','d','e','f'], columns=list('ABCD'))
df1
Out[14]:
  A B C D
a -1.636900 0.966756 0.742416 -1.163262
b 0.035832 -0.960578 0.253173 0.165655
c -1.032465 0.270160 1.445454 0.598161
d 2.112374 -0.890787 -0.308986 -1.187998
e -1.834906 -1.939869 0.924308 -1.150917
f 0.148556 2.410571 0.083520 -2.209039
df.head()
Out[9]:
  A B C D
2013-01-01 -0.542835 2.640071 1.244249 1.613720
2013-01-02 0.270210 0.238108 -1.111091 -0.700783
2013-01-03 -0.681126 -1.618220 -0.221547 0.379695
2013-01-04 -0.490011 -0.301552 1.951446 -0.074140
2013-01-05 -0.549930 0.558058 -0.015088 0.092985
df.tail() #默認是5行
Out[11]:
  A B C D
2013-01-02 0.270210 0.238108 -1.111091 -0.700783
2013-01-03 -0.681126 -1.618220 -0.221547 0.379695
2013-01-04 -0.490011 -0.301552 1.951446 -0.074140
2013-01-05 -0.549930 0.558058 -0.015088 0.092985
2013-01-06 0.761844 -0.938138 0.065372 -0.677193
df.tail(3) #查看后3行
Out[12]:
  A B C D
2013-01-04 -0.490011 -0.301552 1.951446 -0.074140
2013-01-05 -0.549930 0.558058 -0.015088 0.092985
2013-01-06 0.761844 -0.938138 0.065372 -0.677193
df.columns#df的列名
Out[13]:
Index(['A', 'B', 'C', 'D'], dtype='object')df.describe()#統(tǒng)計性描述分析
Out[14]:
  A B C D
count 6.000000 6.000000 6.000000 6.000000
mean -0.205308 0.096388 0.318890 0.105714
std 0.583378 1.474587 1.098568 0.853820
min -0.681126 -1.618220 -1.111091 -0.700783
25% -0.548156 -0.778992 -0.169932 -0.526430
50% -0.516423 -0.031722 0.025142 0.009422
75% 0.080155 0.478071 0.949530 0.308018
max 0.761844 2.640071 1.951446 1.613720
df.T#轉(zhuǎn)置
  2013-01-01 00:00:00 2013-01-02 00:00:00 2013-01-03 00:00:00 2013-01-04 00:00:00 2013-01-05 00:00:00 2013-01-06 00:00:00
A -0.542835 0.270210 -0.681126 -0.490011 -0.549930 0.761844
B 2.640071 0.238108 -1.618220 -0.301552 0.558058 -0.938138
C 1.244249 -1.111091 -0.221547 1.951446 -0.015088 0.065372
D 1.613720 -0.700783 0.379695 -0.074140 0.092985 -0.677193
df.sort_index(axis=1, ascending=False) #以列降序排列
D C B A  
2013-01-01 1.613720 1.244249 2.640071 -0.542835
2013-01-02 -0.700783 -1.111091 0.238108 0.270210
2013-01-03 0.379695 -0.221547 -1.618220 -0.681126
2013-01-04 -0.074140 1.951446 -0.301552 -0.490011
2013-01-05 0.092985 -0.015088 0.558058 -0.549930
2013-01-06 -0.677193 0.065372 -0.938138 0.761844
df.sort_values(by='B') ##按B列的值來排序，默認是升序
A B C D  
2013-01-03 -0.681126 -1.618220 -0.221547 0.379695
2013-01-06 0.761844 -0.938138 0.065372 -0.677193
2013-01-04 -0.490011 -0.301552 1.951446 -0.074140
2013-01-02 0.270210 0.238108 -1.111091 -0.700783
2013-01-05 -0.549930 0.558058 -0.015088 0.092985
2013-01-01 -0.542835 2.640071 1.244249 1.613720
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數(shù)據(jù)分析群

	A	B	C	D
2013-01-01	-0.747037	-0.665933	0.506150	-0.047263
2013-01-02	-0.501075	0.843647	0.506725	-0.499766
2013-01-03	-1.171445	0.816434	0.761552	-0.908022
2013-01-04	-0.226046	-0.472765	3.075716	1.063544
2013-01-05	0.108281	-0.122184	-0.011140	-1.287596
2013-01-06	-1.499848	-0.430267	2.074067	-1.067155

	A	B	C	D
a	-1.636900	0.966756	0.742416	-1.163262
b	0.035832	-0.960578	0.253173	0.165655
c	-1.032465	0.270160	1.445454	0.598161
d	2.112374	-0.890787	-0.308986	-1.187998
e	-1.834906	-1.939869	0.924308	-1.150917
f	0.148556	2.410571	0.083520	-2.209039

	A	B	C	D
2013-01-01	-0.542835	2.640071	1.244249	1.613720
2013-01-02	0.270210	0.238108	-1.111091	-0.700783
2013-01-03	-0.681126	-1.618220	-0.221547	0.379695
2013-01-04	-0.490011	-0.301552	1.951446	-0.074140
2013-01-05	-0.549930	0.558058	-0.015088	0.092985

	A	B	C	D
2013-01-02	0.270210	0.238108	-1.111091	-0.700783
2013-01-03	-0.681126	-1.618220	-0.221547	0.379695
2013-01-04	-0.490011	-0.301552	1.951446	-0.074140
2013-01-05	-0.549930	0.558058	-0.015088	0.092985
2013-01-06	0.761844	-0.938138	0.065372	-0.677193

	A	B	C	D
2013-01-04	-0.490011	-0.301552	1.951446	-0.074140
2013-01-05	-0.549930	0.558058	-0.015088	0.092985
2013-01-06	0.761844	-0.938138	0.065372	-0.677193

	A	B	C	D
count	6.000000	6.000000	6.000000	6.000000
mean	-0.205308	0.096388	0.318890	0.105714
std	0.583378	1.474587	1.098568	0.853820
min	-0.681126	-1.618220	-1.111091	-0.700783
25%	-0.548156	-0.778992	-0.169932	-0.526430
50%	-0.516423	-0.031722	0.025142	0.009422
75%	0.080155	0.478071	0.949530	0.308018
max	0.761844	2.640071	1.951446	1.613720

	2013-01-01 00:00:00	2013-01-02 00:00:00	2013-01-03 00:00:00	2013-01-04 00:00:00	2013-01-05 00:00:00	2013-01-06 00:00:00
A	-0.542835	0.270210	-0.681126	-0.490011	-0.549930	0.761844
B	2.640071	0.238108	-1.618220	-0.301552	0.558058	-0.938138
C	1.244249	-1.111091	-0.221547	1.951446	-0.015088	0.065372
D	1.613720	-0.700783	0.379695	-0.074140	0.092985	-0.677193

D	C	B	A
2013-01-01	1.613720	1.244249	2.640071	-0.542835
2013-01-02	-0.700783	-1.111091	0.238108	0.270210
2013-01-03	0.379695	-0.221547	-1.618220	-0.681126
2013-01-04	-0.074140	1.951446	-0.301552	-0.490011
2013-01-05	0.092985	-0.015088	0.558058	-0.549930
2013-01-06	-0.677193	0.065372	-0.938138	0.761844

A	B	C	D
2013-01-03	-0.681126	-1.618220	-0.221547	0.379695
2013-01-06	0.761844	-0.938138	0.065372	-0.677193
2013-01-04	-0.490011	-0.301552	1.951446	-0.074140
2013-01-02	0.270210	0.238108	-1.111091	-0.700783
2013-01-05	-0.549930	0.558058	-0.015088	0.092985
2013-01-01	-0.542835	2.640071	1.244249	1.613720