pandas的基本用法(一)——数据定义及使用

文章作者：Tyan
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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 pdimport numpy as np# Test 1# 定义序列, pandas中的数据形式通常是float32或float64s = pd.Series([1, 3, 5, np.nan, 44,  1])print sprint s[0]print s[3]# Test 1 result0     1.01     3.02     5.03     NaN4    44.05     1.0dtype: float641.0nan# Test 2# 定义日期列表dates = pd.date_range('20170101', periods = 6)print datesprint dates[5]# Test 2 resultDatetimeIndex(['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DataFramedf = 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         d2017-01-01  1.104994  1.328379  0.410358 -1.6610592017-01-02 -0.642727 -0.152576  1.126191 -0.0053172017-01-03 -0.179257  0.160972 -0.824172 -0.1750272017-01-04  0.838328 -0.500909  0.714592  1.1448002017-01-05  0.803691 -3.979186 -1.037603 -0.7479432017-01-06  1.217289 -0.074413  0.504138 -0.077507   0  1   2   30  0  1   2   31  4  5   6   72  8  9  10  11     A    B  C0  1.0  Foo  31  1.0  Foo  32  1.0  Foo  33  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 resultA    float64B     objectC      int64dtype: objectRangeIndex(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      Ccount  4.0    4.0mean   1.0    3.0std    0.0    0.0min    1.0    3.025%    1.0    3.050%    1.0    3.075%    1.0    3.0max    1.0    3.0       0      1      2      3A      1      1      1      1B      Foo    Foo    Foo    FooC      3      3      3      3       A      B      C0      1.0    3      Foo1      1.0    3      Foo2      1.0    3      Foo3      1.0    3      Foo       C      B      A0      Foo    3      1.01      Foo    3      1.02      Foo    3      1.03      Foo    3      1.0       A      B      C0      1.0    3      Foo1      1.0    3      Foo2      1.0    3      Foo3      1.0    3      Foo