Exam DP-100 topic 3 question 18 discussion

if salesData contains data in pivoted form ,the syntax should be, newsalesData = pd.melt(salesData, id_vars = ...............

Just tried out: pd.melt(salesData, id_vars=['shop'], value_vars=[2017, 2018], var_name='year') works as desired. [2017, 2018] for value_vars is correct. Side note: without 'var_name' parameter a default name is given to column 2.

salesData = pd.melt(salesData, id_vars='shop', value_vars=['2017', '2018'])

I think this question is missing a step of: whateverdfname = pd.DataFrame(....) then we can use salesData =pd.melt(whateverdfname, ...,...) so the second and third answer are correct, first box not sure.

The answer is wrong. It shall be pd.melt(salesData, id_vars=['shop'], value_vars=['2017', '2018'])

import pandas as pd salesData = pd.DataFrame({ 'shop': ['ShopX', 'ShopY', 'ShopZ'], '2017': [34, 65, 48], '2018': [25, 76, 55] }) meltedData = pd.melt(salesData, id_vars=['shop'], value_vars=['2017', '2018'], var_name='year', value_name='value')

Please do not mislead the people. The correct answer should be as below: 1. salesData 2. shop 3. [2017, 2018]

why not YEAR, because we are giving the values of col YEAR i.e., 2017,... ?

Correct answer: salesData shop [2017, 2018]

On exam 2021/7/10

import pandas as pd salesData = pd.DataFrame({'shop': {0: 'shopx', 1: 'shopy', 2: 'shopz'}, '2017': {0: '34', 1: '65', 2: '48'}, '2018': {0: '25', 1: '76', 2: '55'}}) salesData salesData = salesData.reset_index() salesData salesData = pd.melt(salesData, id_vars =['shop'], value_vars=['2017', '2018']) salesData

import pandas as pd df = pd.DataFrame({'shop': {0: 'shopx', 1: 'shopy', 2: 'shopz'}, '2017': {0: '34', 1: '65', 2: '48'}, '2018': {0: '25', 1: '76', 2: '55'}}) df pd.melt(df, id_vars =['shop'], value_vars =['2017', '2018']) /////////////////////////////////////////////////////// ////////////////////////////////////////////////////// shop variable value 0 shopx 2017 34 1 shopy 2017 65 2 shopz 2017 48 3 shopx 2018 25 4 shopy 2018 76 5 shopz 2018 55

Is this a test question that will be included in real exam?

Just tried df = pd.melt(df, id_vars= ['Shop'], value_vars=['2017', '2018']), it returns desired outcome

import pandas as pd salesData = pd.DataFrame({'shop': {0: 'Shop X', 1: 'Shop Y', 2: 'Shop Z'}, '2017': {0: 34, 1: 65, 2: 48}, '2018': {0: 25, 1: 76, 2: 55}}) salesData = pd.melt(salesData,id_vars='shop',value_vars=['2017','2018']) print(salesData) ----------------------------------------------------------------------------------------------------------------------- shop variable value 0 Shop X 2017 34 1 Shop Y 2017 65 2 Shop Z 2017 48 3 Shop X 2018 25 4 Shop Y 2018 76 5 Shop Z 2018 55

salesData is correct

pd.melt(salesData, id_vars=['shop'], value_vars=['year'])