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export data from all over the world in clothing and textile, Papers of Advanced Data Analysis

Export data from all over the world in the clothing and textile industry provides valuable insights into global trade patterns, market trends, and the economic significance of this sector. Here's a description of the export data in the clothing and textile industry: 1. Global Export Volume and Value: Export data reveals the volume and value of clothing and textile products traded between countries worldwide. It provides a comprehensive picture of the scale and magnitude of international trade in this industry. The data showcases the quantities of garments, fabrics, fibers, yarns, and other textile-related products exported globally. 2. Top Exporting Countries: The data identifies the leading countries that dominate the clothing and textile export market. It highlights the major players in terms of export volume and value, indicating their competitiveness and market share. Countries such as China, Bangladesh, Vietnam, India, and the United States are often prominent exporters in this

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2021/2022

Uploaded on 06/09/2023

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Download export data from all over the world in clothing and textile and more Papers Advanced Data Analysis in PDF only on Docsity! National Institute of Fashion Technology (NIFT), PATNA Mithapur Institutional Area, Mithapur Farm Area Patna, PIN - 800001 Department of Fashion Management Studies (FMS) BIG DATA ASSIGNMENT 1 Submitted To - Prof. Kislay Kashyap Submitted By -Mansi Singh BIG DATA SUBMISSION 1 1.Calculate the Dealer margin per unit for each Category, each Gender. STEP 1: Make one column beside Dealer Margin to calculate the Dealer Margin/ per unit and name as Dealer Margin/unit. STEP 2 : Now divide Dealer Margin with Invoice Quantity by using this formula =Dealer Margin/ Invoice Quantity ( =T2/L2 ) T- represent Dealer Margin column and L- represent Invoice Quantity column. STEP 3 : Paste this formula ( =T2/L2 ) to ( =T59/L59 ) to calculate the each category and gender dealer maegin/ unit STEP 4 :To check Dealer margin per unit for each category and each gender we need to create Pivot Table. Select All the data. STEP 5 : Go to Insert. Click on Pivot table it show like this STEP 6 : Now on the right side of the table we can see Pivot Table Fieds in which we have 4 column .i.e. ( Rows, Columns, Value and Filters ) in ROWS select Matl group, in COLUMNS select gender and in VALUES select Dealer Maegin/unit. STEP 7 : Press ENTER it looks like below Table. 2 4.Write Down the formula for counting invoice quantity more than 100. STEP 1: Make one column beside Invoice Quantity to count > 100 invoice quantity and name as invoice quantity > 100. STEP 2 : Now, put this formula =IF(L2>100,1,0) on first row of invoice quantity > 100 column and paste this formula to the whole column. STEP 3 : Make a sum of all the out comes value total is 36 that mean 36 quantity have >100 value. 5.Create a pivot table with Gender in the report filter, category in the column and invoice quantity in the value. 6.Create Data bars in the MRP column for values that are more then 1 lakh. STEP 1 : Select MRP column from U2 to U59. STEP 2 : Select the conditional formatting go to Data bar then go to more. STEP 3 : New Formatting type opne then edit the rule description format all cells based on their value in type enter Number and Value enter 1,00,000. STEP 4: Press enter it look like this 5 7.Using data validation, make the first column of a blank sheet such that it accepts only numbers that are less than 1. STEP 1 : Open new sheet than go to Data Column 6 STEP 2 : Go to Data validation and them settings get open in validation criteria put the vale in Allow like Whole Number in Data enter less that 1 and Maximum is 1. STEP 3 : Click enter Now, enter any value grater that 1 that it shows like this. 8. Insert any three shapes on a blank sheet and group them together. STEP 1 : Open new sheet then go to insert than go to shape make three shapes. STEP 2 : Select them together by pressing ctrl + click Now , right click on selection STEP 3 : Press group and it look like this 7
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