1616402700

In my last post, I mentioned working with groupby technique in Pandas library. I will talk about pivot table in this post. A pivot table is a tool that summarizes the spread data set. This tool combines the data set into a rectangular table using one or more key columns.

Sometimes the difference between pivot tables and groupby is confusing. Pivot tables can be thought of as the multidimensional of groupby grouping.

In summary, I will explain the following topics in this post.

- What is the groupby method in short?
- What is the difference between pivot_table and groupby method?
- What are the functions that can be used with -pivot_table?
- What are multi-level pivot tables?
- What are crosstab tables?
- How to make a sample application with real data set?

Before starting the topic, our Medium page includes posts on data science, artificial intelligence, machine learning, and deep learning. Please don’t forget to follow us on ** Medium** 🌱 to see these posts and the latest posts.

Let’s get started.

#data-preprocessing #python-pandas #pandas-tutorial #pivot-tables #pandas

1616402700

In my last post, I mentioned working with groupby technique in Pandas library. I will talk about pivot table in this post. A pivot table is a tool that summarizes the spread data set. This tool combines the data set into a rectangular table using one or more key columns.

Sometimes the difference between pivot tables and groupby is confusing. Pivot tables can be thought of as the multidimensional of groupby grouping.

In summary, I will explain the following topics in this post.

- What is the groupby method in short?
- What is the difference between pivot_table and groupby method?
- What are the functions that can be used with -pivot_table?
- What are multi-level pivot tables?
- What are crosstab tables?
- How to make a sample application with real data set?

Before starting the topic, our Medium page includes posts on data science, artificial intelligence, machine learning, and deep learning. Please don’t forget to follow us on ** Medium** 🌱 to see these posts and the latest posts.

Let’s get started.

#data-preprocessing #python-pandas #pandas-tutorial #pivot-tables #pandas

1616059380

In this article, we will learn how to use pivot_table() in Pandas with examples. As per pandas official documentation.

Pivot table:

“Create a spreadsheet-style pivot table as a DataFrame”.

The levels in the pivot table will be stored in MultiIndex objects (hierarchical indexes) on the index and columns of the result DataFrame.

It compares input features/columns of data in a tabular form. Let’s have a look at some examples to get a better understanding. There are other ways to get similar results like Pandas Crosstab discussing in my next article but for now, we will use the Cars dataset from Kaggle.

#python #pandas #data-analysis #pandas-dataframe #pivoting

1616583540

A common Excel function made easier in Pandas.

In this short blog post, I will teach you about the different ways you can structure and index your dataset(s) to make it simpler to process or comprehend. The three goals of this blog post are:

- Show the difference between a wide dataframe and a long dataframe.
- Compare simple, flattened index structures and multi-hierarchical index structures.
- Show how to make them yourself utilizing aggregation functions and pivot tables.

#pivot-tables #data-science #pandas

1586702221

In this post, we will learn about pandas’ data structures/objects. Pandas provide two type of data structures:-

Pandas Series is a one dimensional indexed data, which can hold datatypes like integer, string, boolean, float, python object etc. A Pandas Series can hold only one data type at a time. The axis label of the data is called the index of the series. The labels need not to be unique but must be a hashable type. The index of the series can be integer, string and even time-series data. In general, Pandas Series is nothing but a column of an excel sheet with row index being the index of the series.

Pandas dataframe is a primary data structure of pandas. Pandas dataframe is a two-dimensional size mutable array with both flexible row indices and flexible column names. In general, it is just like an excel sheet or SQL table. It can also be seen as a python’s dict-like container for series objects.

#python #python-pandas #pandas-dataframe #pandas-series #pandas-tutorial

1617220260

Every project brings Data Scientist a lot of questions and challenges. When we face a new data set, we don’t know how to describe it clearly, which features correlate with each other, how many outliers we have, and more questions. We start to understand the data set from quick exploratory data analysis (EDA), where we should summarize hundreds of rows and columns. For this step better to have a simple and powerful tool is a plus.

One of the tools which help us save time and avoid frustration is the pivot table. It is useful for the slice, filter, and group data at the speed of inquiry. Also, it is represented the information in a visually appealing way.

In this blog, I want to show your work with pivot tables in Pandas.

#pandas #data-analysis #python #data-science #pivot-tables