Gain insights into conducting meaningful data analysis in Python without prior programming experience. Discover Python fundamentals, data preprocessing, EDA, and predictive analytics for solving business problems.

env.tar.gz

Python3

Ready to move past Excel for complex business analysis? Then you’ll find this course very helpful.

This hands-on introductory Data Science course is aimed at professionals and students who don't have any experience with programming. It will help you advance your career by preparing you to conduct meaningful data analysis in Python on any dataset — large or small.

You’ll begin with the fundamentals of Python, with focus on CSV files in Python, covering concepts like data preprocessing and Exploratory Data Analysis (EDA). In the second half, you'll focus on predictive and inferential analysis using statistical and machine learning techniques, and learn how these techniques can help solve business problems.

Data Science for Non-Programmers

# Bivariate plots
**Bivariate plots** are plots that aim to graph the relationship between two variables. These plots can help us establish relationships and patterns in the data. Some common bivariate plots are:
* *scatter plots*
* *bar plots*
* *histograms*

Let's look at some of these plots and how we can plot them using Pandas and matplotlib. We will be using [Sample Sales Data](https://www.kaggle.com/kyanyoga/sample-sales-data). The data is in *sales_data_sample.csv* file. Have a look at the data.

## Bivariate plots with `dataframe.plot`
In Pandas, we only need to use the `plot` function with the dataframe to plot bivariate plots. The function expects the following arguments: 
* `kind`: the type of plot, i.e., scatter, bar etc.
* `x`: name of the column to place at x-axis.
* `y`: name of the column to place at y-axis.

This lesson will describe the process of plotting bivariate plots of the data from a csv file in Python.

What is Data Science

Python Basics

Handling Tabular Data in Python

Data Cleaning

Exploratory Data Analysis

Statistical Inference

Predictive Models

Machine Learning

Plotting Data 2: Bivariate Plots

Bivariate plots

Bivariate plots with `dataframe.plot`

Plotting Data 2: Bivariate Plots

Bivariate plots

Bivariate plots with dataframe.plot

Bivariate plots with `dataframe.plot`