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Author's profile photo Rahul Mahajan

Data Geek Challenge – District wise,season wise crop production Statistics in India from 1998 to 2003 by using SAP Predictive Analysis

Last week when I saw data geek challenge, I was not much aware about it. Later, I read the blog at http://scn.sap.com/docs/DOC-42585 and since then was crazy about this tool called SAP Predictive Analysis. 

As I am from agricultural background and I like researching on it, I choose this dataset for this blog. In this blog, I will be analyzing the Crop Production Statistics in India from 1998 to 2003 in various ways. I have taken dataset from Data Portal.

Before we start actual analysis, let me ask some question.

Which crop production was highest in India from 1998 to 2003? Why Sugar was leading in exporting compared to Rice?  How was the Potato production happening in India in early 2000?

To answer these questions we can use SAP Predictive analysis tool and simply upload data using any of the below data source. In my example,  I will be using data source in CSV format.

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Define some attributes as measures. Drag measure on Y-Axis and then some other fields on X-axis and then select different views, graphs, pie-charts etc. and do your analysis.

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Following screenshot provides answer to all above questions.

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Let’s see some specific scenarios such as crop wise, state wise, district wise crop production in India


Scenario 1: District, Season and Crop wise Production in India where state is Gujarat

Gujarat being very popular in terms of growth in India from last 5-6 years, I thought let’s find out which district in Gujarat produces which crop and in which season. Based on below screenshot we can see that Surat is leading for Sugarcane not only in particular season but throughout the year.

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Scenario 2: District wise Crop Production in India where state is Maharashtra ( from year 1999 to 2003)

How was the crop production in various districts in Maharashtra state? To answer this question we can select Production on Y axis and put Districts on X Axis first. Then filter the States to Maharashtra only.

From below screenshot we can easily identify that Kolhapur District is ahead of all other districts in Maharashtra and that’s why it’s one of the richest district in state.

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Scenario 3: State Wise (Top 10 State) Rice Production Analysis ( from year 1999 to 2003)

Which state produces maximum rice in India?  Below screenshot clearly depicts that Andhra Pradesh is leading in producing rice.

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Same result can be viewed in different format as shown below.

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Scenario 4: District wise Crop Production in Geographical format ( from year 1999 to 2003)

SAP Predictive analysis also provides a feature where  we can do data analysis based on geographical format. Following screen depicts district wise crop production in Maharashtra State in India.

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Similarly we can have data analysis in pie chart format. Following screen shot depicts year wise Crop Production in Maharashtra State in India. Below analysis is limited to year 1998 to 1999.

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One important point: Till this point we were just doing the analysis of available data in various formats such as Graph, 3D views, Pie Charts, Geographical view etc. but SAP Predictive  Analysis also provide option to predict results based on data. Due to technical problems I could not explore more on it.

Once that technical problem is resolved I will try to update this blog further.

Note: This is just one simple example and does not demonstrate all the functionality available in SAP Predictive Analysis tool.

I hope you like this blog and look forward for your comments and suggestions.

Thanks for reading!!!! 🙂

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      16 Comments
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      Author's profile photo Jitendra Kansal
      Jitendra Kansal

      Really liked your choice.

      Thanks for sharing it.

      Rgrds,

      Jitendra

      Author's profile photo Rahul Mahajan
      Rahul Mahajan
      Blog Post Author

      Thanks Jitendra !

      Author's profile photo Former Member
      Former Member

      Wow its Great Document

      Author's profile photo Rahul Mahajan
      Rahul Mahajan
      Blog Post Author

      Thanks Sushant!

      Author's profile photo Former Member
      Former Member

      Really i like your This Blog and i particularly like Scenario 3 and Scenario 4.

      Thanks for sharing it.

      Regards,

      Viswanathan S

      Author's profile photo Rahul Mahajan
      Rahul Mahajan
      Blog Post Author

      Thanks for comment Viswanathan!

      Author's profile photo Former Member
      Former Member

      Really good work 🙂

      Author's profile photo Rahul Mahajan
      Rahul Mahajan
      Blog Post Author

      Thanks Amala! 🙂

      Author's profile photo Former Member
      Former Member

      Your idea of choosing Indian farming Industry was very appropriate. Awesome analysis Rahul! 🙂

      Author's profile photo Rahul Mahajan
      Rahul Mahajan
      Blog Post Author

      Thanks for the comment Utkarsha! 🙂

      Author's profile photo Former Member
      Former Member

      Hi Rahul,

      Good Day!

      Nice analysis! I appreciate.

      Keep sharing new things. Have a nice day!

      Regards,

      Hari Suseelan

      Author's profile photo Rahul Mahajan
      Rahul Mahajan
      Blog Post Author

      Thanks for appreciating this blog Suseelan Hari! 🙂

      Keep learning and sharing!

      Cheers!!!

      Rahul

      Author's profile photo Former Member
      Former Member

      Hi Rahul,

      Good Day!

      You are welcome! Its my great pleasure to motivate ppl like you. 😆

      Have a fruitful day!

      Regards,

      Hari Suseelan

      Author's profile photo Former Member
      Former Member

      Rahul,

      Great post! We'll be sure to share this with the rest of the #SCN, and Twitter.

      Be sure to check us out, and keep sending those great visualizations!!

      @SAPLumiraExpert

      Author's profile photo Rahul Mahajan
      Rahul Mahajan
      Blog Post Author

      Thanks Irshaad Bijan Adatia!

      Keep Learning,Sharing and Inspiring! 🙂

      Author's profile photo Srinu S
      Srinu S

      Very nice analysis, used good tool very nicely. thanks for your work. Keep sharing 🙂