Are you struggling to perform EDA with R and Python?? Here is an easy way to do exploratory data analysis using Tableau.

您是否正在努力使用R和Python执行EDA？ 这是使用Tableau进行探索性数据分析的简单方法。

Lets Dive in to know the process and look at the analysis !

让我们深入了解该过程并查看分析！

Introduction

介绍

Netflix is the world’s leading internet entertainment service with 158 million paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. I was curious to analyze the content released in Netflix platform which led me to create these simple, interactive and exciting visualizations with Tableau.

Netflix是全球领先的互联网娱乐服务，在190多个国家/地区拥有1.58亿付费会员，他们可以收看各种类型和语言的电视连续剧，纪录片和故事片。 我很好奇地分析了Netflix平台上发布的内容，这促使我使用Tableau创建了这些简单，交互式和令人兴奋的可视化效果。

Data SourceThe dataset used in this EDA project is taken from Kaggle. Click here to download the data.

数据源此EDA项目中使用的数据集取自Kaggle。 点击此处下载数据。

Data Description

资料说明

Data has 12 columns which include show id, title, type, director, cast, country, release year, description, rating and genre of the movies/TV shows. Type column gives if each record is a movie or Tv show. Country column has all the countries a movie or show is released. Each movie or show belongs to one or more genres which is mentioned in the genre column separated by commas.

数据有12列，其中包括电影/电视节目的节目ID，标题，类型，导演，演员，国家/地区，发行年份，描述，等级和流派。 “类型”列给出每个记录是电影还是电视节目。 “国家/地区”列包含已发行电影或节目的所有国家/地区。 每部电影或节目都属于一种或多种类型，在类型栏中以逗号分隔。

Data Transformation

数据转换

In order to visualize top genres or country wise releases, the existing data has to be transformed. We don’t require any coding experience to do this. A simple understanding of Alteryx tool creates a pipeline to transform the data. Lets break down the transformation to 2 steps. Step 1: Convert the text in country and genre columns to multiple columns.Step 2: Transpose the columns to get a record for each genre or country.

为了可视化热门类型或国家/地区发行，必须对现有数据进行转换。 我们不需要任何编码经验。 对Alteryx工具的简单理解可创建用于转换数据的管道。 让我们将转换分解为2个步骤。 第1步：将country和genre列中的文本转换为多列。第2步：转置列以获取每种流派或国家的记录。

See below, the screenshots of the workflow and data sample before and after transformation

参见下文，转换前后的工作流程和数据示例的屏幕截图

探索性数据分析 (EXPLORATORY DATA ANALYSIS)

1. Movies vs TV shows

   电影与电视节目

Netflix platform even has the content which was originally released in 1965. For a better visual I have only displayed the releases from 2000. We observe that initially the percentage of movies is higher than TV shows but from 2019 Netflix has started to focus more on TV shows.

Netflix平台甚至包含最初于1965年发布的内容。为了获得更好的视觉效果，我只显示了2000年以来的版本。我们观察到，电影的百分比最初高于电视节目，但从2019年起，Netflix就开始更多地关注电视节目。

2. Country Wise Releases

2. 明智的国家/地区发布

United states has most total releases ( both movies and TV shows) followed by India and United Kingdom. The interactive dashboard is present here with dynamic parameters to see top N countries of highest releases.

美国的总发行量(电影和电视节目)最多，其次是印度和英国。 此处提供了带有动态参数的交互式仪表板，可以查看N个国家/地区的最高发布版本。

3. Top Genres in Movies vs Tv shows

3.电影与电视节目中的顶尖类型

Movies and Tv shows are predominantly focused on international, dramas and comedies.

电影和电视节目主要集中于国际，戏剧和喜剧。

You can see below the top genres in each category. Click here for movies and here for Tv shows to interact with the chart and see the top N genres in each year or range of years.

您可以在每个类别的顶级类型下面看到。 点击这里为电影和这里的电视节目进行互动与图表，看看每年或几年范围的前N个流派。

4. Country wise releases of each categoryBoth the categories has good presence in United states, India, and UK.

4.每个类别在国家/地区的明智发行情况这两个类别在美国，印度和英国都有良好的影响力。

Can access the complete dashboard from this link and Alteryx workflow is available on my GitHub

可以通过此链接访问完整的仪表板，我的GitHub上提供了Alteryx工作流

结论 (Conclusion)

Netflix has major presence in United states and India. Its focus has shifted recently towards TV shows which was previously on movies. More TV shows released than movies.

Netflix在美国和印度都有重要业务。 最近，它的重点已经转向了以前在电影上的电视节目。 发布的电视节目多于电影。