LET'S DO SOME DATA WORK.
Welcome to Just into Data, a place for data science made simpleR!
Enjoy data science articles on various topics such as Machine Learning, AI, Statistical Modeling, Python Programming.
Pandas read_csv to DataFrames: Python Pandas Tutorial
How to import csv files using pandas with examples
In this tutorial, we’ll show how to use read_csv pandas to import data into Python, with practical examples.
csv (comma-separated values) files are popular to store and transfer data. And pandas is the most popular Python package for data analysis/manipulation. These make pandas read_csv a critical first step to start many data science projects with Python.
You’ll learn from basics to advanced of pandas read_csv, how to:
– import csv files to pandas DataFrame.
– specify data types (low_memory/dtype/converters).
– use a subset of columns/rows.
– assign column names with no header.
This pandas tutorial includes all common cases when loading data using pandas read_csv.
This is an ultimate SQL tutorial to learn SQL for data analysis (from beginner to advanced), with examples for practice.
Following this tutorial, you’ll discover:
– How to learn SQL on a sample database on SQL server, for FREE.
– How to write SELECT statements (all you need to know), SQL joins.
– How to write advanced SQL subqueries, window functions.
How to Download and Install SQL Server and Sample Database: Step-by-Step
Start Learning SQL by setting up a Professional Environment
This is a complete tutorial to download and install a FREE SQL server environment, which is the best way to learn SQL.
Following this guide, you can:
– get your FAQs of SQL answered.
– download and setup Microsoft SQL Server, one of the most popular relational databases on Windows OS.
– install sample database AdventureWorks for practice with real professional simulation.
Whether you want to land those data science jobs successfully or just see how SQL is, setup the SQL environment and start learning!
How to GroupBy with Python Pandas Like a Boss
Best Guide to master Pandas GroupBy with Examples for Data Science
In this tutorial, we are showing how to GroupBy with a foundation Python library, Pandas.
We can’t do data science/machine learning without Group by in Python. It is an essential operation on datasets (DataFrame) when doing data manipulation or analysis.
In this complete guide, you’ll learn :
– What is a Pandas GroupBy (object).
– How to create summary statistics for groups with aggregation functions.
– How to create like-indexed objects of statistics for groups with the transformation method.
– How to use the flexible yet less efficient apply function.
– How to use custom functions for multiple columns.
If you want to master this important technique with hands-on examples, don’t miss this guide.
Decision trees are a very popular machine learning model. The beauty of it comes from its easy-to-understand visualization and fast deployment into production.
Check out this tutorial for a 3 step procedure for visualizing a decision tree in Python.
How to apply Unsupervised Anomaly Detection on bank transactions
A use case of Unsupervised Learning with Python, step-by-step
In this tutorial, we’ll show how to detect outliers or anomalies on unlabeled bank transactions with Python.
– How to identify rare events in an unlabeled dataset using machine learning algorithms: isolation forest (clustering).
– How to visualize the anomaly detection results.
– How to fight crime with anti-money laundering (AML) or fraud analytics in banks
Use case and tip from people with industry experience