Read data with pandas

In Python there's a module that helps you parse data. Data can be in many forms (files, tables, excel, sql, json). There exists so many data sources for historic reasons.

That module to work with data is named the pandas module.

You may know you can use the Pandas module for data analysis. But did you know there are many ways to read data?

pd.read_csv(filename)
pd.read_table(filename)
pd.read_excel(filename)
pd.read_sql(query, connection_object)
pd.read_json(json_string)
pd.read_html(url)
pd.read_clipboard()

Yes, you can read data from many sources. These methods allow you to quickly grab your data

#!/usr/bin/python3 
import pandas as pd
data = pd.read_csv('yourfile.csv', header=None)

If you are using MySQL as source

#!/usr/bin/python3
db = MySQLDatabase(DATABASE_HOST, DATABASE_USER, DATABASE_PASSWORD, DATABASE_NAME)
db_work_view = db.get_work_view()
connection = db_work_view._db_connection
df_people = pd.read_sql('select * from people', connection)

Reading an excel file

df = pd.read_excel('File.xlsx', sheetname='Sheet1')

Well you get the idea. Pandas allows you to quickly fetch data from different data sources. It includes most of the existing data sources.

Related links:

• Python Data Analysis Library
• Learn Python programming
• Python exercises

Comments

[Juan Carlos]

Library	Speed
Pandas read_csv()	20.09
NumPy fromfile()	3.88
NumPy genfromtxt()	4.00
NumPy loadtxt()	1.26
csv (std lib)	0.40
csv (list)	0.38
csv (map)	0.37
Faster_than_csv	0.10

[petercour]

Thanks!