1.) Download the dataset named " Population.csv".2) Read data into Spyder.3) Create variables for each column, each variable is going to store data from appropriate column of the “Population.csv” file (7 variables)Make 3 scatter plots with axis, legend and Title labels for:a) India by Yearb) China by Yearc) USA by Year AutoSaveOffPopulation - Read-Only -Search (Alt+Q)FileHomeInsertDrawPage LayoutFormulasDataReviewViewHelpX CutCalibriv 11v A Aab wrap TextGeneralB CopyPasteConditional Format asCellInsert Delete Formatв I UE E Merge & Center$ • % 9 8 98S Format PainterFormatting vTable v StylesClipboardFontAlignmentNumberStylesCellsA1fxYearADEFH1 TYearIndiaIndia_PercentChinaChina_PercentUSAUSA_Percent2201012342811700.08571895313377050000.0886862213093216660.0878098083201112502887290.08683065413441300000.0891121813115568740.0884443364201212657827900.08790669313506950000.0895474233138309900.089089909201312808461290.08895281913573800000.089990623159937150.08970386201412956041840.08997774313642700000.0904474093183010080.0903588527201513101524030.09098809513712200000.0909081753206351630.0910214688201613245095890.0919851813786650000.0914017583229413110.0916761349201713386588350.09296782313863950000.0919142363249855390.09225644710201813526173280.0939372213927300000.092334233266875010.09273959811201913664177540.09489563813977150000.0926647223282395230.09318018312202013800040000.09583918214026670000.0929930263301390000.09371940413

The python code using spyder IDE is given below:- Below is the Scatter plot for given x and y values:-Population.csv file:- Python code for each plot :- import pandas as pdimport matplotlib.pyplot as plt data= pd.read_csv("Population.csv") #Variablesyears=list(data.Year)india=list(data.India)india_percent=list(data.India_Percent)china=list(data.China)china_percent=list(data.China_Percent)usa=list(data.USA)usa_percent=list(data.USA_Percent) x = yearsy1=indiay2=chinay3=usaplt.xlabel('year')plt.ylabel('population') #Plot -1plt.title('Plot-1: India by Year')plt.scatter(x, y1, c="red",label="India")plt.legend(loc="upper left")plt.show() Output:- #Plot -2plt.title('Plot-1: China by Year')plt.scatter(x, y2,c="blue", label="China")plt.legend(loc="upper left")plt.show() Output:- #Plot -3plt.title('Plot-1: USA by Year')plt.scatter(x, y3,c="black", label="USA")plt.legend(loc="upper left") plt.show() Output:- Explanation:- We can put axis names for x-axis & y-axis is given by:- plt.xlabel('x-axis name')plt.ylabel('y-axis name') We can put title name by:- plt.title('Plot-1: China by Year') We can put legend as:- plt.legend(loc="upper left")If we join all three scatter plots together, then the code is:- Python code:(All 3 Scatter plots):- import pandas as pdimport matplotlib.pyplot as plt data= pd.read_csv("Population.csv") #Creating 7 Variablesyears=list(data.Year)india=list(data.India)india_percent=list(data.India_Percent)china=list(data.China)china_percent=list(data.China_Percent)usa=list(data.USA)usa_percent=list(data.USA_Percent) x = years i=0plt.xlabel('year')plt.ylabel('population')color=["red","blue","black"]countries=["India","China","USA"]for y in [india,china,usa]: plt.scatter(x, list(y), c=color[i], label=str(countries[i]),alpha=0.3, edgecolors='none') i+=1plt.legend(loc="center left") plt.show() Output:-