In the process of Data Analysis, sometimes, we are too engrossed and happy about the available data and try to jump straight into the data and make a lot of analysis and then later try to fit our analysis round business problems whether or not they exist. Hence we try to even make up problems
SAS Studio is a very powerful statistical program which are used by many corporations for various analytic and data science tasks. We briefly want to look at how we can check sum frequency statistics on some columns / attributes in our data. lets set the library name for our working directory where our dataset is
This is a quick to create a dictionary object , write it to a JSON file and then read back the file and convert it to a dictionary and access the items in the dictionary. Credit to : codebasics. You can check him out on Youtube In [3]: # lets create a dictionary of books book
Price Optimisation can be achieved in several ways. I did a simple analysis of how you can use Decision Tree to price optimise a product. This article was published on Data Science Central which can be fully read here: Price Optimisation Using Decision Tree (Regression Tree) – Machine Learning I have received a lot
Sometimes, you need some charts to explore your data and many times when your analysis is done and you want to report, you would most likely want to convey your message using charts and graphs. This is a quick look at some charts which are available and their names: We use this raw data in
There are a couple Free Open Source Data Visualization Tools and Services which you can make use of for your work data exploration and visualization purposes. Below , I list a few ones in no order of importance. Caravel: It is a Python based data exploration and visualization software by Airbnb. It is powerful and
Google has now made Data Studio accessible and you can use it to create pretty cool data visualizations. You can find out more about the free versions and the premium versions here. Google Data Studio In the meantime, you can view a simple dashboard I created for Amazon Product Sourcing here: Amazon product Sourcing Google Studio
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
This is a short scrap notes from the Machine Learning Course taught by Associate Professor, Andrew Ng, Stanford University on Coursera. hypothesis = hØ(x) + Øo + Ø1X Parameters = Øo , Ø1 Our Goal = minimise Ø0 , Ø1 that is the cost function J(Ø0, Ø1) GRADIENT Descent. An algorithm wich minimises the
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
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