文章作者：Tyan
博客：noahsnail.com | CSDN | 简书
本文主要是关于pandas的一些基本用法。
#!/usr/bin/env python
# _*_ coding: utf-8 _*_
import pandas as pd
import numpy as np
# Test 1
# 定义序列, pandas中的数据形式通常是float32或float64
s = pd.Series([1, 3, 5, np.nan, 44, 1])
print s
print s[0]
print s[3]
# Test 1 result
0 1.0
1 3.0
2 5.0
3 NaN
4 44.0
5 1.0
dtype: float64
1.0
nan
# Test 2
# 定义日期列表
dates = pd.date_range('20170101', periods = 6)
print dates
print dates[5]
# Test 2 result
DatetimeIndex(['2017-01-01', '2017-01-02', '2017-01-03', '2017-01-04',
'2017-01-05', '2017-01-06'],
dtype='datetime64[ns]', freq='D')
2017-01-06 00:00:00
# Test 3
# DataFrame类似于numpy的array, 行索引为dates, 列索引为[a, b, c, d]
df = pd.DataFrame(np.random.randn(6, 4), index = dates, columns = ['a', 'b', 'c', 'd'])
print df
# 不指定索引的DataFrame
df = pd.DataFrame(np.arange(12).reshape(3, 4))
print df
# DataFrame的定义
df = pd.DataFrame({'A': 1., 'B': 'Foo', 'C': np.array([3] * 4)})
print df
# Test 3 result
a b c d
2017-01-01 1.104994 1.328379 0.410358 -1.661059
2017-01-02 -0.642727 -0.152576 1.126191 -0.005317
2017-01-03 -0.179257 0.160972 -0.824172 -0.175027
2017-01-04 0.838328 -0.500909 0.714592 1.144800
2017-01-05 0.803691 -3.979186 -1.037603 -0.747943
2017-01-06 1.217289 -0.074413 0.504138 -0.077507
0 1 2 3
0 0 1 2 3
1 4 5 6 7
2 8 9 10 11
A B C
0 1.0 Foo 3
1 1.0 Foo 3
2 1.0 Foo 3
3 1.0 Foo 3
# Test 4
# 查看DataFrame的数据类型
df.dtypes
# 查看DataFrame的索引
df.index
# 查看DataFrame的列索引
df.columns
# 查看DataFrame的值
df.values
# 查看DataFrame的描述
df.describe()
# DataFrame的转置
df.T
# DataFrame的index排序
df.sort_index(axis = 1)
# DataFrame的index排序, 逆序
df.sort_index(axis = 1, ascending = False)
# DataFrame按值排序
df.sort_values(by = 'C')
# Test 4 result
A float64
B object
C int64
dtype: object
RangeIndex(start=0, stop=4, step=1)
Index([u'A', u'B', u'C'], dtype='object')
array([[1.0, 'Foo', 3],
[1.0, 'Foo', 3],
[1.0, 'Foo', 3],
[1.0, 'Foo', 3]], dtype=object)
A C
count 4.0 4.0
mean 1.0 3.0
std 0.0 0.0
min 1.0 3.0
25% 1.0 3.0
50% 1.0 3.0
75% 1.0 3.0
max 1.0 3.0
0 1 2 3
A 1 1 1 1
B Foo Foo Foo Foo
C 3 3 3 3
A B C
0 1.0 3 Foo
1 1.0 3 Foo
2 1.0 3 Foo
3 1.0 3 Foo
C B A
0 Foo 3 1.0
1 Foo 3 1.0
2 Foo 3 1.0
3 Foo 3 1.0
A B C
0 1.0 3 Foo
1 1.0 3 Foo
2 1.0 3 Foo
3 1.0 3 Foo
