Get started with the basics of analytics in Python, the language of choice for data science.

Python Data Analysis and Visualization

Get started with the basics of analytics in Python, the language of choice for data science using Python data structures,  descriptive statistics, and much more.

Data Analysis and Visualization

## Pivot Table

Somewhat like Excel, we can pivot our data using pandas pivot_table functionality. To do so, we will use the `pivot_table()` function.

The `values` parameter is the column being used for aggregation, the `index` parameter is for the index values that creates multiple rows, and the `columns` parameter is for the value on which you want to have multiple columns created.

You can also use the `aggfunc` parameter to pass a function with which to aggregate your pivots.

Let's look at an example:



# Pivot Table

Somewhat like Excel, we can pivot our data using pandas pivot_table functionality. To do so, we will use the `pivot_table()` function.

The `values` parameter is the column being used for aggregation, the `index` parameter is for the index values that creates multiple rows, and the `columns` parameter is for the value on which you want to have multiple columns created.

You can also use the `aggfunc` parameter to pass a function with which to aggregate your pivots.

Let's look at an example:



This lesson explains the possible ways to reshape and arrange the data using Pandas. 

What is Analytics

Python Basics for Analytics

Describing Data

Cleaning Data

Visualizing Data

Reshaping the Data

Pivot Table #