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執行EDA？ 這是使用Tableau進行探索性數據分析的簡單方法。

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

讓我們深入了解該過程并查看分析！

Introduction

介紹

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是全球領先的互聯網娛樂服務，在190多個國家/地區擁有1.58億付費會員，他們可以收看各種類型和語言的電視連續劇，紀錄片和故事片。 我很好奇地分析了Netflix平臺上發布的內容，這促使我使用Tableau創建了這些簡單，交互式和令人興奮的可視化效果。

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

數據源此EDA項目中使用的數據集取自Kaggle。 點擊此處下載數據。

Data Description

資料說明

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.

數據有12列，其中包括電影/電視節目的節目ID，標題，類型，導演，演員，國家/地區，發行年份，描述，等級和流派。 “類型”列給出每個記錄是電影還是電視節目。 “國家/地區”列包含已發行電影或節目的所有國家/地區。 每部電影或節目都屬于一種或多種類型，在類型欄中以逗號分隔。

Data Transformation

數據轉換

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.

為了可視化熱門類型或國家/地區發行，必須對現有數據進行轉換。 我們不需要任何編碼經驗。 對Alteryx工具的簡單理解可創建用于轉換數據的管道。 讓我們將轉換分解為2個步驟。 第1步：將country和genre列中的文本轉換為多列。第2步：轉置列以獲取每種流派或國家的記錄。

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

參見下文，轉換前后的工作流程和數據示例的屏幕截圖

探索性數據分析 (EXPLORATORY DATA ANALYSIS)

1. Movies vs TV shows

   電影與電視節目

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平臺甚至包含最初于1965年發布的內容。為了獲得更好的視覺效果，我只顯示了2000年以來的版本。我們觀察到，電影的百分比最初高于電視節目，但從2019年起，Netflix就開始更多地關注電視節目。

2. Country Wise Releases

2. 明智的國家/地區發布

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.

美國的總發行量(電影和電視節目)最多，其次是印度和英國。 此處提供了帶有動態參數的交互式儀表板，可以查看N個國家/地區的最高發布版本。

3. Top Genres in Movies vs Tv shows

3.電影與電視節目中的頂尖類型

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

電影和電視節目主要集中于國際，戲劇和喜劇。

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.

您可以在每個類別的頂級類型下面看到。 點擊這里為電影和這里的電視節目進行互動與圖表，看看每年或幾年范圍的前N個流派。

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

4.每個類別在國家/地區的明智發行情況這兩個類別在美國，印度和英國都有良好的影響力。

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

可以通過此鏈接訪問完整的儀表板，我的GitHub上提供了Alteryx工作流

結論 (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在美國和印度都有重要業務。 最近，它的重點已經轉向了以前在電影上的電視節目。 發布的電視節目多于電影。