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This article is to share with you about the five practical Pandas skills, which the editor thinks are very practical, so I share them with you to learn. I hope you can get something after reading this article.

Author | RAM DEWANI compilation | VK Source | Analytics Vidhya

Introduction

Efficiency has become a key factor in completing the work in time. One should not spend more than a reasonable amount of time to finish things. Especially when the task involves basic coding. Using the Pandas library can save you time.

Pandas is an open source package. It helps to perform data analysis and data manipulation in Python language. In addition, it provides us with flexible data structures.

Catalogue

Pandas Tip 1-condition selection of rows

Pandas Tip 2-data Storage

Pandas Tip 3-packet data

Pandas skills 4-Pandas map

Conditional formatting of Pandas skill 5-Pandas DataFrame

Pandas Tip 1-condition selection of rows

First of all, data exploration is a necessary step. Pandas provides a quick and simple method for all kinds of analysis. One of the most important techniques is to select rows or filter data based on criteria.

The conditional selection of rows can be based on a single condition or multiple conditions in a single statement separated by logical operators.

For example, I use a dataset about loan forecasts.

We will select a row of clients who have not yet graduated and earn less than £5400. Let's see what we can do.

Video: https://youtu.be/hc4or_RF5M8

Import pandas as pddata = pd.read_csv ('.. / Data/loan_train.csv') data.head () data2 = data.loc [(data ['Education'] = =' Not Graduate') & (data ['ApplicantIncome'] 80 else' black' return 'color:% s'% colorformatting = data.iloc [:, 1:6] .style.applymap (highlight_green) formatting

Code: https://github.com/kunalj101/Data-Science-Hacks/blob/master/Code/Pandas_conditional_formatting.ipynb

In this article, we summarize five tips for Pandas.

These are the five practical Pandas skills. The editor believes that there are some knowledge points that we may see or use in our daily work. I hope you can learn more from this article. For more details, please follow the industry information channel.

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