Pandas series - read csv / txt / excel / mysql data

This code demonstrates:

1. pandas to read plain text files

• Read csv file
• Read txt file

1. pandas read xlsx excel file format
2. mysql data table read pandas

import pandas as pd

1, to read plain text files

1.1 reading CSV, using the default title line, comma separator

fpath = "./datas/ml-latest-small/ratings.csv"

# 使用pd.read_csv读取数据
ratings = pd.read_csv(fpath)

# 查看前几行数据
ratings.head()

	userId	movieId	rating	timestamp
0	1	1	4.0	964982703
1	1	3	4.0	964981247
2	1	6	4.0	964982224
3	1	47	5.0	964983815
4	1	50	5.0	964982931

# 查看数据的形状，返回(行数、列数)
ratings.shape

(100836, 4)

# 查看列名列表
ratings.columns

Index(['userId', 'movieId', 'rating', 'timestamp'], dtype='object')

# 查看索引列
ratings.index

RangeIndex(start=0, stop=100836, step=1)

# 查看每列的数据类型
ratings.dtypes

userId         int64
movieId        int64
rating       float64
timestamp      int64
dtype: object

1.2 read txt file, specify your own delimiters, column names

fpath = "./datas/crazyant/access_pvuv.txt"

pvuv = pd.read_csv(
    fpath,
    sep="\t",
    header=None,
    names=['pdate', 'pv', 'uv']
)

pvuv

	pdate	pv	uv
0	2019-09-10	139	92
1	2019-09-09	185	153
2	2019-09-08	123	59
3	2019-09-07	65	40
4	2019-09-06	157	98
5	2019-09-05	205	151
6	2019-09-04	196	167
7	2019-09-03	216	176
8	2019-09-02	227	148
9	2019-09-01	105	61

2, read the excel file

fpath = "./datas/crazyant/access_pvuv.xlsx"
pvuv = pd.read_excel(fpath)

pvuv

	date	PV	UV
0	2019-09-10	139	92
1	2019-09-09	185	153
2	2019-09-08	123	59
3	2019-09-07	65	40
4	2019-09-06	157	98
5	2019-09-05	205	151
6	2019-09-04	196	167
7	2019-09-03	216	176
8	2019-09-02	227	148
9	2019-09-01	105	61

3, read the MySQL database

import pymysql
conn = pymysql.connect(
        host='127.0.0.1',
        user='root',
        password='12345678',
        database='test',
        charset='utf8'
    )

mysql_page = pd.read_sql("select * from crazyant_pvuv", con=conn)

mysql_page

	pdate	pv	uv
0	2019-09-10	139	92
1	2019-09-09	185	153
2	2019-09-08	123	59
3	2019-09-07	65	40
4	2019-09-06	157	98
5	2019-09-05	205	151
6	2019-09-04	196	167
7	2019-09-03	216	176
8	2019-09-02	227	148
9	2019-09-01	105	61

Code address of this article: https://github.com/peiss/ant-learn-pandas