All Posts by Admin

Python for Data Science –Free Learning Path

It took me a long time to learn Python. The reasons are aplenty on why it was such a long journey. However, hands down, I can tell you the main reasons are due to the vast amount of flexibility with Python. I tried to learn too much at one time instead of focusing on key […]

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  • November 26, 2018
  • Blog

Data Visualization –NBA Highest Points Per Game

NBA All Time Point Leaders This Plotly chart was created using a dataset of NBA players stats from basketball-reference.com. It contains player points, rebounds, assists, starts and etc. I create this visualization by building it in Plotly, based on an initial Python plot created using Matplotlib. I wanted to explore using Plotly cause I thought […]

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Seaborn Histogram

You can easily create and style a histogram in Seaborn with just a few steps. Let’s get started. You will need a few dependencies to ensure that the plot is shown.  The dependencies that you essentially need to load are Matplotlib and Seaborn. However, let’s load the standards such as Pandas and Numpy also in case […]

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Create a Python Heatmap with Seaborn

You can easily create a heatmap using the Seaborn library in Python.  For this tutorial, I’m going to create this using Jupyter Notebooks. The first step is to load the dependencies which are the essential library. import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt %matplotlib inline Now […]

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Google Store Most Installed Apps

The  Google Apps store has a plethora of different apps ranging across a ton of different categories. Here is a visualization created in Tableau that give you an idea of what are the most popular apps on the platform.       The dataset was sourced a Kaggle.com in the form a CSV. I did some light […]

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  • November 4, 2018
  • Blog

Create Pivot Tables with Pandas

One of the key actions for any data analyst is to be able to pivot data tables. Luckily Pandas has an excellent function that will allow you to pivot. To create this spread shit style pivot table, you will need two dependencies with is Numpy and Pandas. However, in newer iterations, you don’t need Numpy. […]

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  • October 28, 2018
  • PANDAS

How to Use CALCULATE in Power BI

Great Uses for CALCULATE in Power BI Calculate is one of the most versatile functions in Power BI. When you begin using anything from simple filters, time intelligence functions or even advanced formulas, often the CALCULATE formulas are leveraged to produce the desired outcome. Let ’s use CALCULATE to filer a column in a table. CALCULATE […]

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How to Fix VLOOKUP Errors

How to Fix VLOOKUP Errors Summary: VLOOKUP function in Excel is the most widely used function and it comes in very handy while looking up the value from different data sources. However, VLOOKUP also has a lot of limitations and specificities, which leads to various problems and errors. In this article, we are going to […]

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  • October 14, 2018
  • Excel

Google Career Listings Visualization

  The data was sourced from Kaggle where a user scraped the Google’s careers. Natural Language Toolkit was used in Python. NLTK and BeautifulSoup were used to clean the dataset and split the twelve hundred plus job listings. The job listings were tokenized into nearly seventy-five thousands words. The stop words were removed from the list […]

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Tableau Directional Vector Map

Directional Vector Map in Tableau Directional maps help to show the trade routes, shipping and a whole host of directional data represented. The best way to represent this is by using the map in Tableau.  Your boss may ask you to visually represent the amount of items shipped to different locations around the globe. We are […]

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