DinaZahran/matplotlib_data_analysis_questions
24
1formatted_text
2"<|user|>3Exercise 1:Read Total profit of all months and show it using a line plot<|end|>4<|assistant|>5```python 6import pandas as pd 7import matplotlib.pyplot as plt 8 9df = pd.read_csv(""D:\\Python\\Articles\\matplotlib\\sales_data.csv"")10profitList = df ['total_profit'].tolist()11monthList = df ['month_number'].tolist()12plt.plot(monthList, profitList, label = 'Month-wise Profit data of last year')13plt.xlabel('Month number')14plt.ylabel('Profit in dollar')15plt.xticks(monthList)16plt.title('Company profit per month')17plt.yticks([100000, 200000, 300000, 400000, 500000])18plt.show() 19 ```<|end|>20"
21"<|user|>22Exercise 2: Get total profit of all months and show line plot with the following Style properties<|end|>23<|assistant|>24```python 25 import pandas as pd26import matplotlib.pyplot as plt 27 28df = pd.read_csv(""D:\\Python\\Articles\\matplotlib\\sales_data.csv"")29profitList = df ['total_profit'].tolist()30monthList = df ['month_number'].tolist()31 32plt.plot(monthList, profitList, label = 'Profit data of last year', 33 color='r', marker='o', markerfacecolor='k', 34 linestyle='--', linewidth=3)35 36plt.xlabel('Month Number')37plt.ylabel('Profit in dollar')38plt.legend(loc='lower right')39plt.title('Company Sales data of last year')40plt.xticks(monthList)41plt.yticks([100000, 200000, 300000, 400000, 500000])42plt.show() 43```<|end|>44"
45"<|user|>46Exercise 3: Read all product sales data and show it using a multiline plot<|end|>47<|assistant|>48```python 49import pandas as pd50import matplotlib.pyplot as plt 51 52df = pd.read_csv(""D:\\Python\\Articles\\matplotlib\\sales_data.csv"")53monthList = df ['month_number'].tolist()54faceCremSalesData = df ['facecream'].tolist()55faceWashSalesData = df ['facewash'].tolist()56toothPasteSalesData = df ['toothpaste'].tolist()57bathingsoapSalesData = df ['bathingsoap'].tolist()58shampooSalesData = df ['shampoo'].tolist()59moisturizerSalesData = df ['moisturizer'].tolist()60 61plt.plot(monthList, faceCremSalesData, label = 'Face cream Sales Data', marker='o', linewidth=3)62plt.plot(monthList, faceWashSalesData, label = 'Face Wash Sales Data', marker='o', linewidth=3)63plt.plot(monthList, toothPasteSalesData, label = 'ToothPaste Sales Data', marker='o', linewidth=3)64plt.plot(monthList, bathingsoapSalesData, label = 'ToothPaste Sales Data', marker='o', linewidth=3)65plt.plot(monthList, shampooSalesData, label = 'ToothPaste Sales Data', marker='o', linewidth=3)66plt.plot(monthList, moisturizerSalesData, label = 'ToothPaste Sales Data', marker='o', linewidth=3)67 68plt.xlabel('Month Number')69plt.ylabel('Sales units in number')70plt.legend(loc='upper left')71plt.xticks(monthList)72plt.yticks([1000, 2000, 4000, 6000, 8000, 10000, 12000, 15000, 18000])73plt.title('Sales data')74plt.show() 75 ```<|end|>76"
77"<|user|>78Exercise 4: Read toothpaste sales data of each month and show it using a scatter plot<|end|>79<|assistant|>80```python 81import pandas as pd82import matplotlib.pyplot as plt 83 84df = pd.read_csv(""D:\\Python\\Articles\\matplotlib\\sales_data.csv"")85monthList = df ['month_number'].tolist()86toothPasteSalesData = df ['toothpaste'].tolist()87plt.scatter(monthList, toothPasteSalesData, label = 'Tooth paste Sales data')88plt.xlabel('Month Number')89plt.ylabel('Number of units Sold')90plt.legend(loc='upper left')91plt.title(' Tooth paste Sales data')92plt.xticks(monthList)93plt.grid(True, linewidth= 1, linestyle=""--"")94plt.show() 95```<|end|>96"
97"<|user|>98Exercise 5: Read face cream and facewash product sales data and show it using the bar chart<|end|>99<|assistant|>100```python 101import pandas as pd102import matplotlib.pyplot as plt 103 104df = pd.read_csv(""D:\\Python\\Articles\\matplotlib\\sales_data.csv"")105monthList = df ['month_number'].tolist()106faceCremSalesData = df ['facecream'].tolist()107faceWashSalesData = df ['facewash'].tolist()108 109plt.bar([a-0.25 for a in monthList], faceCremSalesData, width= 0.25, label = 'Face Cream sales data', align='edge')110plt.bar([a+0.25 for a in monthList], faceWashSalesData, width= -0.25, label = 'Face Wash sales data', align='edge')111plt.xlabel('Month Number')112plt.ylabel('Sales units in number')113plt.legend(loc='upper left')114plt.title(' Sales data')115 116plt.xticks(monthList)117plt.grid(True, linewidth= 1, linestyle=""--"")118plt.title('Facewash and facecream sales data')119plt.show() 120 ```<|end|>121"
122"<|user|>123Exercise 6: Read sales data of bathing soap of all months and show it using a bar chart. Save this plot to your hard disk<|end|>124<|assistant|>125```python 126import pandas as pd127import matplotlib.pyplot as plt 128 129df = pd.read_csv(""D:\\Python\\Articles\\matplotlib\\sales_data.csv"")130monthList = df ['month_number'].tolist()131bathingsoapSalesData = df ['bathingsoap'].tolist()132plt.bar(monthList, bathingsoapSalesData)133plt.xlabel('Month Number')134plt.ylabel('Sales units in number')135plt.title(' Sales data')136plt.xticks(monthList)137plt.grid(True, linewidth= 1, linestyle=""--"")138plt.title('bathingsoap sales data')139plt.savefig('D:\Python\Articles\matplotlib\sales_data_of_bathingsoap.png', dpi=150)140plt.show() 141```<|end|>142"
143"<|user|>144Exercise 7: Read the total profit of each month and show it using the histogram to see the most common profit ranges<|end|>145<|assistant|>146```python 147import pandas as pd148import matplotlib.pyplot as plt 149 150df = pd.read_csv(""D:\\Python\\Articles\\matplotlib\\sales_data.csv"")151profitList = df ['total_profit'].tolist()152labels = ['low', 'average', 'Good', 'Best']153profit_range = [150000, 175000, 200000, 225000, 250000, 300000, 350000]154plt.hist(profitList, profit_range, label = 'Profit data')155plt.xlabel('profit range in dollar')156plt.ylabel('Actual Profit in dollar')157plt.legend(loc='upper left')158plt.xticks(profit_range)159plt.title('Profit data')160plt.show() 161 ```<|end|>162"
163"<|user|>164Exercise 8: Calculate total sale data for last year for each product and show it using a Pie chart<|end|>165<|assistant|>166```python 167import pandas as pd168import matplotlib.pyplot as plt 169 170df = pd.read_csv(""D:\\Python\\Articles\\matplotlib\\sales_data.csv"")171monthList = df ['month_number'].tolist()172 173labels = ['FaceCream', 'FaseWash', 'ToothPaste', 'Bathing soap', 'Shampoo', 'Moisturizer']174salesData = [df ['facecream'].sum(), df ['facewash'].sum(), df ['toothpaste'].sum(), 175 df ['bathingsoap'].sum(), df ['shampoo'].sum(), df ['moisturizer'].sum()]176plt.axis(""equal"")177plt.pie(salesData, labels=labels, autopct='%1.1f%%')178plt.legend(loc='lower right')179plt.title('Sales data')180plt.show() 181```<|end|>182"
183"<|user|>184Exercise 9: Read Bathing soap facewash of all months and display it using the Subplot<|end|>185<|assistant|>186```python 187 import pandas as pd188import matplotlib.pyplot as plt 189 190df = pd.read_csv(""D:\\Python\\Articles\\matplotlib\\sales_data.csv"")191monthList = df ['month_number'].tolist()192bathingsoap = df ['bathingsoap'].tolist()193faceWashSalesData = df ['facewash'].tolist()194 195f, axarr = plt.subplots(2, sharex=True)196axarr[0].plot(monthList, bathingsoap, label = 'Bathingsoap Sales Data', color='k', marker='o', linewidth=3)197axarr[0].set_title('Sales data of a Bathingsoap')198axarr[1].plot(monthList, faceWashSalesData, label = 'Face Wash Sales Data', color='r', marker='o', linewidth=3)199axarr[1].set_title('Sales data of a facewash')200 201plt.xticks(monthList)202plt.xlabel('Month Number')203plt.ylabel('Sales units in number')204plt.show() 205```<|end|>206"
207"<|user|>208Exercise Question 10: Read all product sales data and show it using the stack plot<|end|>209<|assistant|>210```python 211import pandas as pd212import matplotlib.pyplot as plt 213 214df = pd.read_csv(""D:\\Python\\Articles\\matplotlib\\sales_data.csv"")215monthList = df ['month_number'].tolist()216 217faceCremSalesData = df ['facecream'].tolist()218faceWashSalesData = df ['facewash'].tolist()219toothPasteSalesData = df ['toothpaste'].tolist()220bathingsoapSalesData = df ['bathingsoap'].tolist()221shampooSalesData = df ['shampoo'].tolist()222moisturizerSalesData = df ['moisturizer'].tolist()223 224plt.plot([],[],color='m', label='face Cream', linewidth=5)225plt.plot([],[],color='c', label='Face wash', linewidth=5)226plt.plot([],[],color='r', label='Tooth paste', linewidth=5)227plt.plot([],[],color='k', label='Bathing soap', linewidth=5)228plt.plot([],[],color='g', label='Shampoo', linewidth=5)229plt.plot([],[],color='y', label='Moisturizer', linewidth=5)230 231plt.stackplot(monthList, faceCremSalesData, faceWashSalesData, toothPasteSalesData, 232 bathingsoapSalesData, shampooSalesData, moisturizerSalesData, 233 colors=['m','c','r','k','g','y'])234 235plt.xlabel('Month Number')236plt.ylabel('Sales unints in Number')237plt.title('Alll product sales data using stack plot')238plt.legend(loc='upper left')239plt.show() 240 ```<|end|>241"
242"<|user|>243Show moisturizer sales data of each month using a scatter plot.<|end|>244<|assistant|>245```python246import pandas as pd247import matplotlib.pyplot as plt248 249df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")250monthList = df['month_number'].tolist()251salesData = df['moisturizer'].tolist()252plt.scatter(monthList, salesData, label='moisturizer Sales data')253plt.xlabel('Month Number')254plt.ylabel('Number of units Sold')255plt.legend(loc='upper left')256plt.title('moisturizer Sales data')257plt.xticks(monthList)258plt.grid(True, linewidth=1, linestyle=""--"")259plt.show()260```<|end|>261"
262"<|user|>263Show shampoo sales data of each month using a line chart.<|end|>264<|assistant|>265```python266import pandas as pd267import matplotlib.pyplot as plt268 269df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")270monthList = df['month_number'].tolist()271salesData = df['shampoo'].tolist()272plt.plot(monthList, salesData, label='shampoo Sales data', marker='o')273plt.xlabel('Month Number')274plt.ylabel('Number of units Sold')275plt.legend(loc='upper left')276plt.title('shampoo Sales data')277plt.xticks(monthList)278plt.grid(True, linewidth=1, linestyle=""--"")279plt.show()280```<|end|>281"
282"<|user|>283Show toothpaste sales data of each month using a line chart.<|end|>284<|assistant|>285```python286import pandas as pd287import matplotlib.pyplot as plt288 289df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")290monthList = df['month_number'].tolist()291salesData = df['toothpaste'].tolist()292plt.plot(monthList, salesData, label='toothpaste Sales data', marker='o')293plt.xlabel('Month Number')294plt.ylabel('Number of units Sold')295plt.legend(loc='upper left')296plt.title('toothpaste Sales data')297plt.xticks(monthList)298plt.grid(True, linewidth=1, linestyle=""--"")299plt.show()300```<|end|>301"
302"<|user|>303Visualize facewash sales data of each month with a pie chart.<|end|>304<|assistant|>305```python306import pandas as pd307import matplotlib.pyplot as plt308 309df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")310salesData = df['facewash'].tolist()311monthList = df['month_number'].tolist()312plt.pie(salesData, labels=monthList, autopct='%1.1f%%')313plt.title('facewash Sales data')314plt.show()315```<|end|>316"
317"<|user|>318Visualize soap sales data of each month with a line chart.<|end|>319<|assistant|>320```python321import pandas as pd322import matplotlib.pyplot as plt323 324df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")325monthList = df['month_number'].tolist()326salesData = df['soap'].tolist()327plt.plot(monthList, salesData, label='soap Sales data', marker='o')328plt.xlabel('Month Number')329plt.ylabel('Number of units Sold')330plt.legend(loc='upper left')331plt.title('soap Sales data')332plt.xticks(monthList)333plt.grid(True, linewidth=1, linestyle=""--"")334plt.show()335```<|end|>336"
337"<|user|>338Visualize facewash sales data of each month with a histogram.<|end|>339<|assistant|>340```python341import pandas as pd342import matplotlib.pyplot as plt343 344df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")345salesData = df['facewash'].tolist()346plt.hist(salesData, bins=5, edgecolor='black')347plt.xlabel('Sales Data')348plt.ylabel('Frequency')349plt.title('facewash Sales data')350plt.show()351```<|end|>352"
353"<|user|>354Visualize toothpaste sales data of each month with a histogram.<|end|>355<|assistant|>356```python357import pandas as pd358import matplotlib.pyplot as plt359 360df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")361salesData = df['toothpaste'].tolist()362plt.hist(salesData, bins=5, edgecolor='black')363plt.xlabel('Sales Data')364plt.ylabel('Frequency')365plt.title('toothpaste Sales data')366plt.show()367```<|end|>368"
369"<|user|>370Create a histogram chart for shampoo sales data of each month.<|end|>371<|assistant|>372```python373import pandas as pd374import matplotlib.pyplot as plt375 376df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")377salesData = df['shampoo'].tolist()378plt.hist(salesData, bins=5, edgecolor='black')379plt.xlabel('Sales Data')380plt.ylabel('Frequency')381plt.title('shampoo Sales data')382plt.show()383```<|end|>384"
385"<|user|>386Visualize moisturizer sales data of each month with a bar chart.<|end|>387<|assistant|>388```python389import pandas as pd390import matplotlib.pyplot as plt391 392df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")393monthList = df['month_number'].tolist()394salesData = df['moisturizer'].tolist()395plt.bar(monthList, salesData, label='moisturizer Sales data')396plt.xlabel('Month Number')397plt.ylabel('Number of units Sold')398plt.legend(loc='upper left')399plt.title('moisturizer Sales data')400plt.xticks(monthList)401plt.grid(True, linewidth=1, linestyle=""--"")402plt.show()403```<|end|>404"
405"<|user|>406Visualize toothpaste sales data of each month with a bar chart.<|end|>407<|assistant|>408```python409import pandas as pd410import matplotlib.pyplot as plt411 412df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")413monthList = df['month_number'].tolist()414salesData = df['toothpaste'].tolist()415plt.bar(monthList, salesData, label='toothpaste Sales data')416plt.xlabel('Month Number')417plt.ylabel('Number of units Sold')418plt.legend(loc='upper left')419plt.title('toothpaste Sales data')420plt.xticks(monthList)421plt.grid(True, linewidth=1, linestyle=""--"")422plt.show()423```<|end|>424"
425"<|user|>426Visualize shampoo sales data of each month with a histogram.<|end|>427<|assistant|>428```python429import pandas as pd430import matplotlib.pyplot as plt431 432df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")433salesData = df['shampoo'].tolist()434plt.hist(salesData, bins=5, edgecolor='black')435plt.xlabel('Sales Data')436plt.ylabel('Frequency')437plt.title('shampoo Sales data')438plt.show()439```<|end|>440"
441"<|user|>442Read moisturizer sales data and plot a pie chart chart for each month.<|end|>443<|assistant|>444```python445import pandas as pd446import matplotlib.pyplot as plt447 448df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")449salesData = df['moisturizer'].tolist()450monthList = df['month_number'].tolist()451plt.pie(salesData, labels=monthList, autopct='%1.1f%%')452plt.title('moisturizer Sales data')453plt.show()454```<|end|>455"
456"<|user|>457Create a histogram chart for toothpaste sales data of each month.<|end|>458<|assistant|>459```python460import pandas as pd461import matplotlib.pyplot as plt462 463df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")464salesData = df['toothpaste'].tolist()465plt.hist(salesData, bins=5, edgecolor='black')466plt.xlabel('Sales Data')467plt.ylabel('Frequency')468plt.title('toothpaste Sales data')469plt.show()470```<|end|>471"
472"<|user|>473Visualize toothpaste sales data of each month with a scatter plot.<|end|>474<|assistant|>475```python476import pandas as pd477import matplotlib.pyplot as plt478 479df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")480monthList = df['month_number'].tolist()481salesData = df['toothpaste'].tolist()482plt.scatter(monthList, salesData, label='toothpaste Sales data')483plt.xlabel('Month Number')484plt.ylabel('Number of units Sold')485plt.legend(loc='upper left')486plt.title('toothpaste Sales data')487plt.xticks(monthList)488plt.grid(True, linewidth=1, linestyle=""--"")489plt.show()490```<|end|>491"
492"<|user|>493Show toothpaste sales data of each month using a scatter plot.<|end|>494<|assistant|>495```python496import pandas as pd497import matplotlib.pyplot as plt498 499df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")500monthList = df['month_number'].tolist()501salesData = df['toothpaste'].tolist()502plt.scatter(monthList, salesData, label='toothpaste Sales data')503plt.xlabel('Month Number')504plt.ylabel('Number of units Sold')505plt.legend(loc='upper left')506plt.title('toothpaste Sales data')507plt.xticks(monthList)508plt.grid(True, linewidth=1, linestyle=""--"")509plt.show()510```<|end|>511"
512"<|user|>513Visualize toothpaste sales data of each month with a histogram.<|end|>514<|assistant|>515```python516import pandas as pd517import matplotlib.pyplot as plt518 519df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")520salesData = df['toothpaste'].tolist()521plt.hist(salesData, bins=5, edgecolor='black')522plt.xlabel('Sales Data')523plt.ylabel('Frequency')524plt.title('toothpaste Sales data')525plt.show()526```<|end|>527"
528"<|user|>529Visualize moisturizer sales data of each month with a line chart.<|end|>530<|assistant|>531```python532import pandas as pd533import matplotlib.pyplot as plt534 535df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")536monthList = df['month_number'].tolist()537salesData = df['moisturizer'].tolist()538plt.plot(monthList, salesData, label='moisturizer Sales data', marker='o')539plt.xlabel('Month Number')540plt.ylabel('Number of units Sold')541plt.legend(loc='upper left')542plt.title('moisturizer Sales data')543plt.xticks(monthList)544plt.grid(True, linewidth=1, linestyle=""--"")545plt.show()546```<|end|>547"
548"<|user|>549Create a pie chart chart for soap sales data of each month.<|end|>550<|assistant|>551```python552import pandas as pd553import matplotlib.pyplot as plt554 555df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")556salesData = df['soap'].tolist()557monthList = df['month_number'].tolist()558plt.pie(salesData, labels=monthList, autopct='%1.1f%%')559plt.title('soap Sales data')560plt.show()561```<|end|>562"
563"<|user|>564Create a histogram chart for facewash sales data of each month.<|end|>565<|assistant|>566```python567import pandas as pd568import matplotlib.pyplot as plt569 570df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")571salesData = df['facewash'].tolist()572plt.hist(salesData, bins=5, edgecolor='black')573plt.xlabel('Sales Data')574plt.ylabel('Frequency')575plt.title('facewash Sales data')576plt.show()577```<|end|>578"
579"<|user|>580Show moisturizer sales data of each month using a pie chart.<|end|>581<|assistant|>582```python583import pandas as pd584import matplotlib.pyplot as plt585 586df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")587salesData = df['moisturizer'].tolist()588monthList = df['month_number'].tolist()589plt.pie(salesData, labels=monthList, autopct='%1.1f%%')590plt.title('moisturizer Sales data')591plt.show()592```<|end|>593"
594"<|user|>595Read soap sales data and plot a bar chart chart for each month.<|end|>596<|assistant|>597```python598import pandas as pd599import matplotlib.pyplot as plt600 601df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")602monthList = df['month_number'].tolist()603salesData = df['soap'].tolist()604plt.bar(monthList, salesData, label='soap Sales data')605plt.xlabel('Month Number')606plt.ylabel('Number of units Sold')607plt.legend(loc='upper left')608plt.title('soap Sales data')609plt.xticks(monthList)610plt.grid(True, linewidth=1, linestyle=""--"")611plt.show()612```<|end|>613"
614"<|user|>615Show shampoo sales data of each month using a pie chart.<|end|>616<|assistant|>617```python618import pandas as pd619import matplotlib.pyplot as plt620 621df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")622salesData = df['shampoo'].tolist()623monthList = df['month_number'].tolist()624plt.pie(salesData, labels=monthList, autopct='%1.1f%%')625plt.title('shampoo Sales data')626plt.show()627```<|end|>628"
629"<|user|>630Create a histogram chart for toothpaste sales data of each month.<|end|>631<|assistant|>632```python633import pandas as pd634import matplotlib.pyplot as plt635 636df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")637salesData = df['toothpaste'].tolist()638plt.hist(salesData, bins=5, edgecolor='black')639plt.xlabel('Sales Data')640plt.ylabel('Frequency')641plt.title('toothpaste Sales data')642plt.show()643```<|end|>644"
645"<|user|>646Create a histogram chart for soap sales data of each month.<|end|>647<|assistant|>648```python649import pandas as pd650import matplotlib.pyplot as plt651 652df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")653salesData = df['soap'].tolist()654plt.hist(salesData, bins=5, edgecolor='black')655plt.xlabel('Sales Data')656plt.ylabel('Frequency')657plt.title('soap Sales data')658plt.show()659```<|end|>660"
661"<|user|>662Read toothpaste sales data and plot a histogram chart for each month.<|end|>663<|assistant|>664```python665import pandas as pd666import matplotlib.pyplot as plt667 668df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")669salesData = df['toothpaste'].tolist()670plt.hist(salesData, bins=5, edgecolor='black')671plt.xlabel('Sales Data')672plt.ylabel('Frequency')673plt.title('toothpaste Sales data')674plt.show()675```<|end|>676"
677"<|user|>678Read toothpaste sales data and plot a scatter plot chart for each month.<|end|>679<|assistant|>680```python681import pandas as pd682import matplotlib.pyplot as plt683 684df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")685monthList = df['month_number'].tolist()686salesData = df['toothpaste'].tolist()687plt.scatter(monthList, salesData, label='toothpaste Sales data')688plt.xlabel('Month Number')689plt.ylabel('Number of units Sold')690plt.legend(loc='upper left')691plt.title('toothpaste Sales data')692plt.xticks(monthList)693plt.grid(True, linewidth=1, linestyle=""--"")694plt.show()695```<|end|>696"
697"<|user|>698Read shampoo sales data and plot a bar chart chart for each month.<|end|>699<|assistant|>700```python701import pandas as pd702import matplotlib.pyplot as plt703 704df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")705monthList = df['month_number'].tolist()706salesData = df['shampoo'].tolist()707plt.bar(monthList, salesData, label='shampoo Sales data')708plt.xlabel('Month Number')709plt.ylabel('Number of units Sold')710plt.legend(loc='upper left')711plt.title('shampoo Sales data')712plt.xticks(monthList)713plt.grid(True, linewidth=1, linestyle=""--"")714plt.show()715```<|end|>716"
717"<|user|>718Create a pie chart chart for soap sales data of each month.<|end|>719<|assistant|>720```python721import pandas as pd722import matplotlib.pyplot as plt723 724df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")725salesData = df['soap'].tolist()726monthList = df['month_number'].tolist()727plt.pie(salesData, labels=monthList, autopct='%1.1f%%')728plt.title('soap Sales data')729plt.show()730```<|end|>731"
732"<|user|>733Read shampoo sales data and plot a histogram chart for each month.<|end|>734<|assistant|>735```python736import pandas as pd737import matplotlib.pyplot as plt738 739df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")740salesData = df['shampoo'].tolist()741plt.hist(salesData, bins=5, edgecolor='black')742plt.xlabel('Sales Data')743plt.ylabel('Frequency')744plt.title('shampoo Sales data')745plt.show()746```<|end|>747"
748"<|user|>749Read toothpaste sales data of each month and show it using a scatter plot.<|end|>750<|assistant|>751```python752import pandas as pd753import matplotlib.pyplot as plt754 755df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")756monthList = df['month_number'].tolist()757salesData = df['toothpaste'].tolist()758plt.scatter(monthList, salesData, label='toothpaste Sales data')759plt.xlabel('Month Number')760plt.ylabel('Number of units Sold')761plt.legend(loc='upper left')762plt.title('toothpaste Sales data')763plt.xticks(monthList)764plt.grid(True, linewidth=1, linestyle=""--"")765plt.show()766```<|end|>767"
768"<|user|>769Create a line chart chart for moisturizer sales data of each month.<|end|>770<|assistant|>771```python772import pandas as pd773import matplotlib.pyplot as plt774 775df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")776monthList = df['month_number'].tolist()777salesData = df['moisturizer'].tolist()778plt.plot(monthList, salesData, label='moisturizer Sales data', marker='o')779plt.xlabel('Month Number')780plt.ylabel('Number of units Sold')781plt.legend(loc='upper left')782plt.title('moisturizer Sales data')783plt.xticks(monthList)784plt.grid(True, linewidth=1, linestyle=""--"")785plt.show()786```<|end|>787"
788"<|user|>789Create a line chart chart for facewash sales data of each month.<|end|>790<|assistant|>791```python792import pandas as pd793import matplotlib.pyplot as plt794 795df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")796monthList = df['month_number'].tolist()797salesData = df['facewash'].tolist()798plt.plot(monthList, salesData, label='facewash Sales data', marker='o')799plt.xlabel('Month Number')800plt.ylabel('Number of units Sold')801plt.legend(loc='upper left')802plt.title('facewash Sales data')803plt.xticks(monthList)804plt.grid(True, linewidth=1, linestyle=""--"")805plt.show()806```<|end|>807"
808"<|user|>809Read moisturizer sales data and plot a line chart chart for each month.<|end|>810<|assistant|>811```python812import pandas as pd813import matplotlib.pyplot as plt814 815df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")816monthList = df['month_number'].tolist()817salesData = df['moisturizer'].tolist()818plt.plot(monthList, salesData, label='moisturizer Sales data', marker='o')819plt.xlabel('Month Number')820plt.ylabel('Number of units Sold')821plt.legend(loc='upper left')822plt.title('moisturizer Sales data')823plt.xticks(monthList)824plt.grid(True, linewidth=1, linestyle=""--"")825plt.show()826```<|end|>827"
828"<|user|>829Read soap sales data and plot a bar chart chart for each month.<|end|>830<|assistant|>831```python832import pandas as pd833import matplotlib.pyplot as plt834 835df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")836monthList = df['month_number'].tolist()837salesData = df['soap'].tolist()838plt.bar(monthList, salesData, label='soap Sales data')839plt.xlabel('Month Number')840plt.ylabel('Number of units Sold')841plt.legend(loc='upper left')842plt.title('soap Sales data')843plt.xticks(monthList)844plt.grid(True, linewidth=1, linestyle=""--"")845plt.show()846```<|end|>847"
848"<|user|>849Visualize moisturizer sales data of each month with a line chart.<|end|>850<|assistant|>851```python852import pandas as pd853import matplotlib.pyplot as plt854 855df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")856monthList = df['month_number'].tolist()857salesData = df['moisturizer'].tolist()858plt.plot(monthList, salesData, label='moisturizer Sales data', marker='o')859plt.xlabel('Month Number')860plt.ylabel('Number of units Sold')861plt.legend(loc='upper left')862plt.title('moisturizer Sales data')863plt.xticks(monthList)864plt.grid(True, linewidth=1, linestyle=""--"")865plt.show()866```<|end|>867"
868"<|user|>869Visualize soap sales data of each month with a line chart.<|end|>870<|assistant|>871```python872import pandas as pd873import matplotlib.pyplot as plt874 875df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")876monthList = df['month_number'].tolist()877salesData = df['soap'].tolist()878plt.plot(monthList, salesData, label='soap Sales data', marker='o')879plt.xlabel('Month Number')880plt.ylabel('Number of units Sold')881plt.legend(loc='upper left')882plt.title('soap Sales data')883plt.xticks(monthList)884plt.grid(True, linewidth=1, linestyle=""--"")885plt.show()886```<|end|>887"
888"<|user|>889Read facewash sales data and plot a bar chart chart for each month.<|end|>890<|assistant|>891```python892import pandas as pd893import matplotlib.pyplot as plt894 895df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")896monthList = df['month_number'].tolist()897salesData = df['facewash'].tolist()898plt.bar(monthList, salesData, label='facewash Sales data')899plt.xlabel('Month Number')900plt.ylabel('Number of units Sold')901plt.legend(loc='upper left')902plt.title('facewash Sales data')903plt.xticks(monthList)904plt.grid(True, linewidth=1, linestyle=""--"")905plt.show()906```<|end|>907"
908"<|user|>909Show shampoo sales data of each month using a scatter plot.<|end|>910<|assistant|>911```python912import pandas as pd913import matplotlib.pyplot as plt914 915df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")916monthList = df['month_number'].tolist()917salesData = df['shampoo'].tolist()918plt.scatter(monthList, salesData, label='shampoo Sales data')919plt.xlabel('Month Number')920plt.ylabel('Number of units Sold')921plt.legend(loc='upper left')922plt.title('shampoo Sales data')923plt.xticks(monthList)924plt.grid(True, linewidth=1, linestyle=""--"")925plt.show()926```<|end|>927"
928"<|user|>929Read toothpaste sales data of each month and show it using a scatter plot.<|end|>930<|assistant|>931```python932import pandas as pd933import matplotlib.pyplot as plt934 935df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")936monthList = df['month_number'].tolist()937salesData = df['toothpaste'].tolist()938plt.scatter(monthList, salesData, label='toothpaste Sales data')939plt.xlabel('Month Number')940plt.ylabel('Number of units Sold')941plt.legend(loc='upper left')942plt.title('toothpaste Sales data')943plt.xticks(monthList)944plt.grid(True, linewidth=1, linestyle=""--"")945plt.show()946```<|end|>947"
948"<|user|>949Read soap sales data and plot a histogram chart for each month.<|end|>950<|assistant|>951```python952import pandas as pd953import matplotlib.pyplot as plt954 955df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")956salesData = df['soap'].tolist()957plt.hist(salesData, bins=5, edgecolor='black')958plt.xlabel('Sales Data')959plt.ylabel('Frequency')960plt.title('soap Sales data')961plt.show()962```<|end|>963"
964"<|user|>965Visualize soap sales data of each month with a pie chart.<|end|>966<|assistant|>967```python968import pandas as pd969import matplotlib.pyplot as plt970 971df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")972salesData = df['soap'].tolist()973monthList = df['month_number'].tolist()974plt.pie(salesData, labels=monthList, autopct='%1.1f%%')975plt.title('soap Sales data')976plt.show()977```<|end|>978"
979"<|user|>980Read moisturizer sales data and plot a pie chart chart for each month.<|end|>981<|assistant|>982```python983import pandas as pd984import matplotlib.pyplot as plt985 986df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")987salesData = df['moisturizer'].tolist()988monthList = df['month_number'].tolist()989plt.pie(salesData, labels=monthList, autopct='%1.1f%%')990plt.title('moisturizer Sales data')991plt.show()992```<|end|>993"
994"<|user|>995Show moisturizer sales data of each month using a bar chart.<|end|>996<|assistant|>997```python998import pandas as pd999import matplotlib.pyplot as plt1000 1001df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")1002monthList = df['month_number'].tolist()1003salesData = df['moisturizer'].tolist()1004plt.bar(monthList, salesData, label='moisturizer Sales data')1005plt.xlabel('Month Number')1006plt.ylabel('Number of units Sold')1007plt.legend(loc='upper left')1008plt.title('moisturizer Sales data')1009plt.xticks(monthList)1010plt.grid(True, linewidth=1, linestyle=""--"")1011plt.show()1012```<|end|>1013"
1014"<|user|>1015Read moisturizer sales data of each month and show it using a line chart.<|end|>1016<|assistant|>1017```python1018import pandas as pd1019import matplotlib.pyplot as plt1020 1021df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")1022monthList = df['month_number'].tolist()1023salesData = df['moisturizer'].tolist()1024plt.plot(monthList, salesData, label='moisturizer Sales data', marker='o')1025plt.xlabel('Month Number')1026plt.ylabel('Number of units Sold')1027plt.legend(loc='upper left')1028plt.title('moisturizer Sales data')1029plt.xticks(monthList)1030plt.grid(True, linewidth=1, linestyle=""--"")1031plt.show()1032```<|end|>1033"
1034"<|user|>1035Read moisturizer sales data and plot a scatter plot chart for each month.<|end|>1036<|assistant|>1037```python1038import pandas as pd1039import matplotlib.pyplot as plt1040 1041df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")1042monthList = df['month_number'].tolist()1043salesData = df['moisturizer'].tolist()1044plt.scatter(monthList, salesData, label='moisturizer Sales data')1045plt.xlabel('Month Number')1046plt.ylabel('Number of units Sold')1047plt.legend(loc='upper left')1048plt.title('moisturizer Sales data')1049plt.xticks(monthList)1050plt.grid(True, linewidth=1, linestyle=""--"")1051plt.show()1052```<|end|>1053"
1054"<|user|>1055Read shampoo sales data of each month and show it using a line chart.<|end|>1056<|assistant|>1057```python1058import pandas as pd1059import matplotlib.pyplot as plt1060 1061df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")1062monthList = df['month_number'].tolist()1063salesData = df['shampoo'].tolist()1064plt.plot(monthList, salesData, label='shampoo Sales data', marker='o')1065plt.xlabel('Month Number')1066plt.ylabel('Number of units Sold')1067plt.legend(loc='upper left')1068plt.title('shampoo Sales data')1069plt.xticks(monthList)1070plt.grid(True, linewidth=1, linestyle=""--"")1071plt.show()1072```<|end|>1073"
1074"<|user|>1075Read shampoo sales data and plot a bar chart chart for each month.<|end|>1076<|assistant|>1077```python1078import pandas as pd1079import matplotlib.pyplot as plt1080 1081df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")1082monthList = df['month_number'].tolist()1083salesData = df['shampoo'].tolist()1084plt.bar(monthList, salesData, label='shampoo Sales data')1085plt.xlabel('Month Number')1086plt.ylabel('Number of units Sold')1087plt.legend(loc='upper left')1088plt.title('shampoo Sales data')1089plt.xticks(monthList)1090plt.grid(True, linewidth=1, linestyle=""--"")1091plt.show()1092```<|end|>1093"
1094"<|user|>1095Show shampoo sales data of each month using a bar chart.<|end|>1096<|assistant|>1097```python1098import pandas as pd1099import matplotlib.pyplot as plt1100 1101df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")1102monthList = df['month_number'].tolist()1103salesData = df['shampoo'].tolist()1104plt.bar(monthList, salesData, label='shampoo Sales data')1105plt.xlabel('Month Number')1106plt.ylabel('Number of units Sold')1107plt.legend(loc='upper left')1108plt.title('shampoo Sales data')1109plt.xticks(monthList)1110plt.grid(True, linewidth=1, linestyle=""--"")1111plt.show()1112```<|end|>1113"
1114"<|user|>1115Visualize soap sales data of each month with a line chart.<|end|>1116<|assistant|>1117```python1118import pandas as pd1119import matplotlib.pyplot as plt1120 1121df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")1122monthList = df['month_number'].tolist()1123salesData = df['soap'].tolist()1124plt.plot(monthList, salesData, label='soap Sales data', marker='o')1125plt.xlabel('Month Number')1126plt.ylabel('Number of units Sold')1127plt.legend(loc='upper left')1128plt.title('soap Sales data')1129plt.xticks(monthList)1130plt.grid(True, linewidth=1, linestyle=""--"")1131plt.show()1132```<|end|>1133"
1134"<|user|>1135Show shampoo sales data of each month using a pie chart.<|end|>1136<|assistant|>1137```python1138import pandas as pd1139import matplotlib.pyplot as plt1140 1141df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")1142salesData = df['shampoo'].tolist()1143monthList = df['month_number'].tolist()1144plt.pie(salesData, labels=monthList, autopct='%1.1f%%')1145plt.title('shampoo Sales data')1146plt.show()1147```<|end|>1148"
1149"<|user|>1150Create a histogram chart for soap sales data of each month.<|end|>1151<|assistant|>1152```python1153import pandas as pd1154import matplotlib.pyplot as plt1155 1156df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")1157salesData = df['soap'].tolist()1158plt.hist(salesData, bins=5, edgecolor='black')1159plt.xlabel('Sales Data')1160plt.ylabel('Frequency')1161plt.title('soap Sales data')1162plt.show()1163```<|end|>1164"
1165"<|user|>1166Show shampoo sales data of each month using a line chart.<|end|>1167<|assistant|>1168```python1169import pandas as pd1170import matplotlib.pyplot as plt1171 1172df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")1173monthList = df['month_number'].tolist()1174salesData = df['shampoo'].tolist()1175plt.plot(monthList, salesData, label='shampoo Sales data', marker='o')1176plt.xlabel('Month Number')1177plt.ylabel('Number of units Sold')1178plt.legend(loc='upper left')1179plt.title('shampoo Sales data')1180plt.xticks(monthList)1181plt.grid(True, linewidth=1, linestyle=""--"")1182plt.show()1183```<|end|>1184"
1185"<|user|>1186Read facewash sales data of each month and show it using a pie chart.<|end|>1187<|assistant|>1188```python1189import pandas as pd1190import matplotlib.pyplot as plt1191 1192df = pd.read_csv(""D:\Python\Articles\matplotlib\sales_data.csv"")1193salesData = df['facewash'].tolist()1194monthList = df['month_number'].tolist()1195plt.pie(salesData, labels=monthList, autopct='%1.1f%%')1196plt.title('facewash Sales data')1197plt.show()1198```<|end|>1199"
1200"<|user|>