Python – Page 2 – DataPandas

Save Multiple Pandas DataFrames to One Single Excel Sheet Side by Side or Dowwards – XlsxWriter

This tutorial is just to illustrate how to save Python Pandas dataframe into one excel work SHEET . You can save it column-wise, that is side by side or row-wise, that is downwards, one dataframe after the other. In [110]:

import sqlalchemy

import pyodbc

from pandas import DataFrame

from bokeh.plotting import figure, output_file, show

import pandas as pd

In [111]:

df = DataFrame

## connect to SqlServer Database and get information.

try:

import urllib

params = urllib.quote_plus("DRIVER={SQL Server Native Client 11.0};SERVER=.\MSSQLSERVER_ENT;DATABASE=Antrak;Trusted_Connection=yes;")

engine = sqlalchemy.create_engine('mssql+pyodbc:///?odbc_connect=%s"' % params)

resoverall = engine.execute("SELECT top 10 * FROM FlightBookingsMain")

df = df(resoverall.fetchall())

df.columns = resoverall.keys()

except (RuntimeError, TypeError, NameError):

print('Error in Conneccting')

print(RuntimeError, TypeError, NameError)

finally:

print("connected")

connected

In [112]:

1 2	#lets look at the head of the dataframe df.head()

Out[112]: First Name Last Name

October 5, 2016 No Comments

Save Python Pivot Table in Excel Sheets ExcelWriter

Untitled This is a quick script on how to save Python pivot_table in an excel file. Credit to pbpython In [1]:

import sqlalchemy

import pyodbc

from pandas import DataFrame

import pandas as pd

In [2]:

df = DataFrame

## connect to SqlServer Database and get information.

try:

import urllib

params = urllib.quote_plus("DRIVER={SQL Server Native Client 11.0};SERVER=.\MSSQLSERVER_ENT;DATABASE=Antrak;Trusted_Connection=yes;")

engine = sqlalchemy.create_engine('mssql+pyodbc:///?odbc_connect=%s"' % params)

resoverall = engine.execute("SELECT * FROM FlightBookingsMain")

df = df(resoverall.fetchall())

df.columns = resoverall.keys()

except (RuntimeError, TypeError, NameError):

print('Error in Conneccting')

print(RuntimeError, TypeError, NameError)

finally:

print("connected")

connected

In [8]:

df.head()

Out[8]: First Name Last Name Sex Phone Fax Email Address Booking Date Departure Date Arrival Date Address1 … Number of Passengers Total Cost Currency Numeric Code

October 5, 2016 No Comments

Python Pandas Pivot Table Index location Percentage calculation on Two columns

pivot table for year on year This is a quick example of how to use pivot_table, to calculate year on year percentage sales . In [162]:

import sqlalchemy

import pyodbc

import numpy as np

from pandas import DataFrame

from bokeh.plotting import figure, output_file, show

import pandas as pd

In [163]:

df = DataFrame

## connect to SqlServer Database and get information.

try:

import urllib

params = urllib.quote_plus("DRIVER={SQL Server Native Client 11.0};SERVER=.\MSSQLSERVER_ENT;DATABASE=Antrak;Trusted_Connection=yes;")

engine = sqlalchemy.create_engine('mssql+pyodbc:///?odbc_connect=%s"' % params)

resoverall = engine.execute("SELECT * FROM FlightBookingsMain")

df = df(resoverall.fetchall())

df.columns = resoverall.keys()

except (RuntimeError, TypeError, NameError):

print('Error in Conneccting')

print(RuntimeError, TypeError, NameError)

finally:

print("connected")

connected

In [164]:

1 2	#lets check the head df.head()

Out[164]: First Name Last Name Sex Phone Fax Email Address Booking Date Departure Date Arrival Date Address1 … Number of Passengers

October 5, 2016 No Comments

Python Bokeh plotting Data Exploration Visualization And Pivot Tables Analysis

This is a quick walk through Bokeh data exploration and visualization and also python pivot_tables (credit to pbpython on the pivot_tables).Visualization Dashboard In [49]:

import sqlalchemy

import pyodbc

from pandas import DataFrame

from bokeh.plotting import figure, output_file, show

import pandas as pd

In [50]:

df = DataFrame

## connect to SqlServer Database and get information.

try:

import urllib

params = urllib.quote_plus("DRIVER={SQL Server Native Client 11.0};SERVER=.\MSSQLSERVER_ENT;DATABASE=Antrak;Trusted_Connection=yes;")

engine = sqlalchemy.create_engine('mssql+pyodbc:///?odbc_connect=%s"' % params)

resoverall = engine.execute("SELECT top 10 * FROM FlightBookingsMain")

df = df(resoverall.fetchall())

df.columns = resoverall.keys()

except (RuntimeError, TypeError, NameError):

print('Error in Conneccting')

print(RuntimeError, TypeError, NameError)

finally:

print("connected")

connected

In [51]:

1 2	#lets look at the head of the dataframe df.head()

Out[51]: First Name Last Name Sex Phone Fax Email Address Booking Date Departure Date Arrival Date Address1 … Number of Passengers Total Cost Currency

October 4, 2016 No Comments

Python PyQt Gui Basics Button Window PyQt4 Pt1

This is just some quick scrap notes on the basics of Python GUI building using PyQt. In [1]:

import sys

from PyQt4 import QtGui, QtCore # to help add buttons

#app = QtGui.QApplication(sys.argv)

#window = QtGui.QWidget()

##set the posstion and size of the window

#window.setGeometry(50, 50, 500, 500)

##lets set the title

#window.setWindowTitle('Date Incrementor')

#window.show()

class Window(QtGui.QMainWindow):

def __init__(self):

super(Window, self).__init__()

self.setGeometry(50,50, 500, 500)

self.setWindowTitle("Date incrementor")

# self.setWindowIcon(QtGui.QIcon('logo.png'))

#self.show()

self.home()

def home(self):

#create and name a button

btn = QtGui.QPushButton("Quit", self)

#define what we will do when the button is clicked

#btn.clicked.connect(QtCore.QCoreApplication.instance().quit)

btn.clicked.connect(self.closeapplication)

#lets resisze the button

btn.resize(100,100)

#lets position the button

btn.move(100,100)

#lets show the button

self.show()

#lets create custom methods

def closeapplication(self):

print('Application closed')

sys.exit()

the ‘init‘ statements runs anytime we call call the Window class we have created and it runs all the code in the Window class the _init__ method calls the super constructor and then sets

September 28, 2016 No Comments

Basic Plotting Using Bokeh Python Pandas Library – Scatter, Line Visualizations

Bokeh is a powerful framework for data visualization in Python. Here I take a look at straightforward plotting and visualization using this powerful library. Credit to PythonHow. You can check him out on Youtube bokeh.models #It is a low level interface which involves a lot of work bokeh.plotting # It is a middle level interface bokeh.chart #

September 26, 2016 No Comments

Python

Python Pandas Groupby function agg Series GroupbyObject

Group By FunctionThis is a quick look at Python groupby function. Very powerful and useful function. We will take a simple look at it here. Credits to Data School , creator of Python course materials. lets import sample dataset In [18]:

1	import pandas as pd

In [19]:

1	drinks = pd.read_csv('http://bit.ly/drinksbycountry')

In [20]:

1 2	#lets check the head drinks.head()

Out[20]: country beer_servings spirit_servings wine_servings total_litres_of_pure_alcohol continent

September 9, 2016 No Comments

Data Science

Python iloc, loc, ix Data Retrieving Selection Functions

Pandas iloc, loc, and ix functions are very powerful ways to quickly select data from your dataframe. Today , we take a quick look at these 3 functions. Credits to Data School, you can check him out in Youtube In [1]:

1	import pandas as pd

In [2]:

1 2	#lets get this public dataset and play with it ufo = pd.read_csv('http://bit.ly/uforeports')

In [3]:

1 2	#lets examine the head ufo.head()

Out[3]: City Colors Reported Shape Reported State

September 5, 2016 No Comments

Data Science

Natural Language Processing Machine Learning Algorithm Model Python – NLP

In this guide, we take a look at Natural Language Processing, NLP in Python. Natural Language is a very extensive topic and very powerful machine learning algorithm you can build. This is very useful in many areas of most industries. Credits to Jose Portilla, creator of Learning Python for Data Analysis and Visualization course on Udemy

September 4, 2016 No Comments

Save Multiple Pandas DataFrames to One Single Excel Sheet Side by Side or Dowwards – XlsxWriter

Save Python Pivot Table in Excel Sheets ExcelWriter

Python Pandas Pivot Table Index location Percentage calculation on Two columns

Python Bokeh plotting Data Exploration Visualization And Pivot Tables Analysis

Python PyQt Gui Basics Button Window PyQt4 Pt1

Basic Plotting Using Bokeh Python Pandas Library – Scatter, Line Visualizations

Python Pandas Groupby function agg Series GroupbyObject

Python iloc, loc, ix Data Retrieving Selection Functions

Natural Language Processing Machine Learning Algorithm Model Python – NLP

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