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
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;”)
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
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
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
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 #
This is a guide on Python List comprehension. List comprehension is a great way to write simple and easy to read Python codes. You can use it dictionaries and sets as well. Credits to Corey Schafer , creator of Python course materials. lets create a list In [115]: num = range(10) num Out[115]: [0, 1,
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]: import pandas as pd In [19]: drinks = pd.read_csv(‘http://bit.ly/drinksbycountry’) In [20]: #lets check the head
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]: import pandas as pd In [2]: #lets get this public dataset and play with it
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
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