Create a dashboard website using HTML and Bootstrap to make visualizations of weather data using CSV...

Question

Create a dashboard website using HTML and Bootstrap to make visualizations of weather data using CSV file provide. Please provide the code in an .html file. Please see attached instructions and CSV file.

Please provide well commented code. Please provide the code in a .html file. Latitude - Latitude Analysis Dashboard with Attitude For this homework we’ll be creating a visualization dashboard website using visualizations. Specifically, we’ll be plotting weather data using the cities csv file. In building this dashboard, we’ll create individual pages for each plot and a means by which we can navigate between them. These pages will contain the visualizations and their corresponding explanations. We’ll also have a landing page, a page where we can see a comparison of all of the plots, and another page where we can view the data used to build them. Website Requirements For reference, see the “Screenshots” section below. The website must consist of 7 pages total, including: · A landing containing: · An explanation of the project. · Links to each visualizations page. · Four visualization pages, each with: · A descriptive title and heading tag. · The plot/visualization itself for the selected comparison. · A paragraph describing the plot and its significance. · A “Comparisons” page that: · Contains all of the visualizations on the same page so we can easily visually compare them. · Uses a bootstrap grid for the visualizations. · The grid must be two visualizations across on screens medium and larger, and 1 across on extra-small and small screens. · A “Data” page that: · Displays a responsive table containing the data used in the visualizations. · The table must be a bootstrap table component. · The data must come from exporting the .csv file as HTML, or converting it to HTML. Try using a tool you already know, pandas. Pandas has a nifty method approprately called to_html that allows you to generate a HTML table from a pandas dataframe. See the documentation here The website must, at the top of every page, have a navigation menu that: · Has the name of the site on the left of the nav which allows users to return to the landing page from any page. · Contains a dropdown on the right of the navbar named “Plots” which provides links to each individual visualization page. · Provides two more links on the right: “Comparisons” which links to the comparisons page, and “Data” which links to the data page. · Is responsive (using media queries). The nav must have similar behavior as the screenshots “Navigation Menu” section (notice the background color change). Considerations · You must use bootstrap. This includes using the bootstrap navbar component for the header on every page, the bootstrap table component for the data page, and the bootstrap grid for responsiveness on the comparison page. · Be sure to use a CSS media query for the navigation menu. · Feel free to take some liberty in the visual aspects, but keep the core functionality the same. Screenshots This section contains screenshots of each page that must be built, at varying screen widths. These are a guide; you can meet the requirements without having the pages look exactly like the below images. Landing page Large screen: Small screen: Comparisons page Large screen: Small screen: Data page Large screen: Small screen: Visualization pages You’ll build four of these, one for each visualization. Here’s an example of one: Large screen: Small screen: Navigation menu Large screen: Small screen:

cities-54r1ylct.csv hw11-web-bootstrap-and-html-wapdnexg.docx

Ayush · Accepted Answer

homework/1.png
homework/2.png
homework/3.png
homework/4.png
homework/comparsion.html
    
    
        Lattitude
        
          
        
       
      
        
          
            		
                    
                      Plots
                    
                    
                      Max Temperature
                      Humidity
                      Cloudiness
                      wind Speed

		
                Comparsion
              
		
                Data

          
              
            
                
                    
                     Plots
                    
                  
                    
                      Max Temperature
                Humidity
                Cloudiness
                wind Speed

                  		
                    Comparsion
                  
		
                    Data

      
          
          
          
              
                  
                  Comparsion:Lattitude vs.X
                  
                  Click any plot to get in depth analysis
                  
                    
                        
                          
                         vs.Max Temperature
 
                        
                        
                           vs. Humidity
                          
 

                
                  
                      
                          vs. Cloudiness
                      
                      
                         vs. Wind Speed
 

      
   
homework/data.html
	
        Lattitude
        
          
        
       
      
        
          
		
					
					  Plots
					
					
						Max Temperature
						Humidity
						Cloudiness
						wind Speed
					
				  
		
				Comparsion
			  
		
				Data
			  
          
          
              
            
                
                        
                         Plots
                        
                      
                        
                          Max Temperature
                    Humidity
                    Cloudiness
                    wind Speed

                  		
                    Comparsion
                  
		
                    Data

	
		Data
        The following table includes all of the data during plotting in this project
        
	
		City_Id
				City		Cloudiness		Country		Date		Humidity		Lat		Lng		Max Temp		Wind Speed
		0		jacareacanga		0		BR		1528902000		62		-6.22		-57.76		89.6		6.93
		1		kaitangata		100		NZ		1528905304		94		-46.28		169.85		42.61		5.64
		2		goulburn		20		AU		1528905078		91		-34.75		149.72		44.32		10.11
		3		lata		76		IN		1528905305		89		30.78		78.62		59.89		0.94
		4		chokurdakh		0		RU		1528905306		88		70.62		147.9		32.17		2.95
		5		martyush		92		RU		1528905306		94		56.4		61.89		55.03		9.33
		6		hobart		20		AU		1528902000		87		-42.88		147.33		44.6		8.05
		7		broken hill		0		AU		1528905311		88		-31.97		141.45		44.5		7.31
		8		harnosand		0		SE		1528903200		44		62.63		17.94		60.8		13.87
		9		tuatapere		0		NZ		1528905312		100		-46.13		167.69		38.92		3.4
		10		puerto ayora		90		EC		1528902000		69		-0.74		-90.35		77		13.87
		11		havre-saint-pierre		75		CA		1528902000		58		50.23		-63.6		53.6		19.46
		12		punta arenas		0		CL		1528902000		100		-53.16		-70.91		35.6		9.17
		13		tasiilaq		75		GL		1528901400		60		65.61		-37.64		39.2		2.24
		14		chapais		40		CA		1528902000		38		49.78		-74.86		59		10.29
		15		avarua		40		CK		1528902000		56		-21.21		-159.78		73.4		10.29
		16		hofn		75		IS		1528902000		87		64.25		-15.21		51.8		8.05
		17		yukamenskoye		92		RU		1528905315		98		57.89		52.24		56.65		10.22
		18		khandbari		80		NP		1528905315		67		27.38		87.21		44.59		1.39
		19		bethel		1		US		1528901580		93		60.79		-161.76		44.6		8.05
		20		ushuaia		75		AR		1528902000		64		-54.81		-68.31		41		3.36
		21		east london		0		ZA		1528902000		37		-33.02		27.91		69.8		5.82
		22		bluff		76		AU		1528905321		76		-23.58		149.07		61.96		4.74
		23		mount isa		75		AU		1528902000		100		-20.73		139.49		64.4		3.29
		24		pevek		0		RU		1528905321		71		69.7		170.27		36.94		6.98
		25		gao		24		ML		1528905321		16		16.28		-0.04		110.02		4.97
		26		cabo san lucas		75		MX		1528901160		74		22.89		-109.91		84.2		10.29
		27		sao filipe		0		CV		1528905323		88		14.9		-24.5		75.73		13.02
		28		tiksi		44		RU		1528905298		58		71.64		128.87		57.73		10.11
		29		busselton		92		AU		1528905323		100		-33.64		115.35		60.43		10.56
		30		alofi		76		NU		1528902000		88		-19.06		-169.92		71.6		3.36
		31		ola		75		RU		1528902000		100		59.58		151.3		42.8		7.76
		32		atar		20		MR		1528902000		19		20.52		-13.05		91.4		9.17
		33		rikitea		0		PF		1528905325		100		-23.12		-134.97		73.57		8.66
		34		hermanus		0		ZA		1528905325		24		-34.42		19.24		77.17		8.66
		35		ponta delgada		75		PT		1528903800		88		37.73		-25.67		71.6		12.75
		36		bambari		24		CF		1528905326		84		5.77		20.68		81.85		7.65
		37		cap malheureux		75		MU		1528902000		69		-19.98		57.61		75.2		14.99
		38		puerto escondido		75		MX		1528901100		65		15.86		-97.07		80.6		3.36
		39		qaanaaq		32		GL		1528905330		100		77.48		-69.36		31.45		6.31
		40		new norfolk		20		AU		1528902000		87		-42.78		147.06		44.6		8.05
		41		najran		40		SA		1528902000		13		17.54		44.22		98.6		11.41
		42		isla mujeres		90		MX		1528904340		100		21.23		-86.73		75.2		16.11
		43		mar del plata		0		AR		1528905297		100		-46.43		-67.52		32.53		7.31
		44		provideniya		0		RU		1528905332		91		64.42		-173.23		40.63		10.78
		45		jamestown		12		AU		1528905333		88		-33.21		138.6		43.15		10.89
		46		medicine hat		20		CA		1528902000		34		50.04		-110.68		66.2		14.99
		47		katsuura		8		JP		1528905334		88		33.93		134.5		62.05		7.54
		48		aklavik		20		CA		1528902000		53		68.22		-135.01		51.8		11.41
		49		tuktoyaktuk		20		CA		1528902000		61		69.44		-133.03		46.4		6.93
		50		kapaa		90		US		1528901760		88		22.08		-159.32		75.2		14.99
		51		mildura		0		AU		1528905300		92		-34.18		142.16		45.67		9.66
		52		souillac		75		FR		1528903800		49		45.6		-0.6		73.4		10.29
		53		lorengau		100		PG		1528905336		100		-2.02		147.27		80.59		3.85
		54		praia		20		BR		1528902000		47		-20.25		-43.81		82.4		3.36
		55		port alfred		0		ZA		1528905338		50		-33.59		26.89		76.54		7.2
		56		barranca		0		PE		1528905339		98		-10.75		-77.76		61.87		9.89
		57		nome		40		US		1528902900		70		30.04		-94.42		87.8		3.36
		58		matay		0		EG		1528905339		23		28.42		30.79		97.69		6.98
		59		saskylakh		48		RU		1528905339		55		71.97		114.09		59.53		5.86
		60		itarema		0		BR		1528905340		61		-2.92		-39.92		88.33		12.57
		61		butaritari		56		KI		1528905340		100		3.07		172.79		81.13		7.31
		62		peniche		20		PT		1528903800		64		39.36		-9.38		75.2		12.75
		63		beloha		0		MG		1528905340		57		-25.17		45.06		71.95		16.37
		64		anadyr		0		RU		1528902000		57		64.73		177.51		48.2		4.47
		65		luderitz		12		NA		1528905342		64		-26.65		15.16		64.03		17.38
		66		rochester		1		US		1528902960		37		44.02		-92.46		73.4		6.93
		67		bosaso		0		SO		1528905347		86		11.28		49.18		89.77		3.96
		68		faanui		0		PF		1528905347		100		-16.48		-151.75		79.96		11.79
		69		grindavik		75		IS		1528902000		70		63.84		-22.43		48.2		5.82
		70		margate		20		AU		1528902000		87		-43.03		147.26		44.6		8.05
		71		marsh harbour		88		BS		1528905349		95		26.54		-77.06		82.39		10
		72		comodoro rivadavia		40		AR		1528902000		60		-45.87		-67.48		42.8		9.17
		73		upernavik		92		GL		1528905350		100		72.79		-56.15		29.29		3.74
		74		uige		0		AO		1528905350		29		-7.61		15.06		86.8		3.18
		75		bredasdorp		0		ZA		1528902000		23		-34.53		20.04		82.4		5.82
		76		bodden town		40		KY		1528902000		78		19.28		-81.25		80.6		16.11
		77		guerrero negro		44		MX		1528905350		88		27.97		-114.04		63.85		3.74
		78		bilma		0		NE		1528905351		12		18.69		12.92		110.47		4.63
		79		carnarvon		0		ZA		1528905351		30		-30.97		22.13		60.43		14.25
		80		ponta do sol		12		BR		1528905352		72		-20.63		-46		78.25		3.96
		81		vila franca do campo		75		PT		1528903800		88		37.72		-25.43		71.6		12.75
		82		puerto del rosario		20		ES		1528903800		60		28.5		-13.86		73.4		17.22
		83		sitka		20		US		1528905353		92		37.17		-99.65		74.02		5.97
		84		camacha		75		PT		1528903800		72		33.08		-16.33		68		16.11
		85		saint-philippe		1		CA		1528902900		54		45.36		-73.48		78.8		11.41
		86		port blair		92		IN		1528905357		97		11.67		92.75		84.37		25.1
		87		albany		90		US		1528903860		68		42.65		-73.75		69.8		3.36
		88		barrow		88		AR		1528905182		72		-38.31		-60.23		50.26		8.21
		89		qorveh		92		IR		1528905357		22		35.17		47.8		76.72		3.18
		90		san jeronimo		90		PE		1528902000		81		-13.65		-73.37		46.4		2.39
		91		mataura		24		NZ		1528905299		79		-46.19		168.86		25.69		3.18
		92		buala		64		SB		1528905359		100		-8.15		159.59		78.7		4.18
		93		eyl		20		SO		1528905359		57		7.98		49.82		86.62		22.41
		94		abu dhabi		0		AE		1528902000		29		24.47		54.37		98.6		16.11
		95		tahe		92		CN		1528905359		98		52.34		124.71		51.43		2.17
		96		chuy		80		UY		1528905099		93		-33.69		-53.46		52.87		28.9
		97		dzerzhinskoye		8		RU		1528905360		69		56.84		95.22		65.11		3.85
		98		vanavara		0		RU		1528905360		50		60.35		102.28		64.21		5.64
		99		muros		40		ES		1528903800		72		42.77		-9.06		66.2		10.29
		100		auchel		0		FR		1528903800		49		50.51		2.47		68		3.36
		101		bubaque		40		GW		1528902000		55		11.28		-15.83		91.4		11.41
		102		khatanga		8		RU		1528905361		65		71.98		102.47		60.97		4.63
		103		los banos		1		US		1528904100		67		37.06		-120.85		75.2		4.74
		104		labuhan		12		ID		1528905361		95		-2.54		115.51		72.94		1.83
		105		saint-paul		75		FR		1528903800		56		45.22		1.9		68		14.99
		106		petatlan		90		MX		1528901220		74		17.52		-101.27		84.2		1.83
		107		baykit		36		RU		1528905366		68		61.68		96.39		63.94		4.29
		108		dalby		75		AU		1528902000		93		-27.18		151.26		53.6		2.24
		109		yellowknife		90		CA		1528902540		93		62.45		-114.38		46.4		8.05
		110		hilo		75		US		1528901580		88		19.71		-155.08		66.2		5.82
		111		turukhansk		36		RU		1528905297		76		65.8		87.96		66.37		6.42
		112		dingle		68		PH		1528905368		82		11		122.67		79.96		8.21
		113		dillon		1		US		1528901580		44		45.22		-112.64		57.2		5.82
		114		labytnangi		64		RU		1528905370		75		66.66		66.39		47.11		17.49
		115		gigmoto		36		PH		1528905370		98		13.78		124.39		83.56		17.6
		116		nouakchott		68		MR		1528905371		76		18.08		-15.98		76.72		1.39
		117		rumoi		92		JP		1528905371		100		43.93		141.67		44.41		8.1
		118		dikson		32		RU		1528905373		100		73.51		80.55		31.09		13.13
		119		chinsali		0		ZM		1528905377		36		-10.55		32.07		73.39		9.22
		120		georgetown		75		GY		1528902000		78		6.8		-58.16		82.4		9.17
		121		tooele		1		US		1528902900		35		40.53		-112.3		73.4		9.17
		122		nikolskoye		40		RU		1528902000		41		59.7		30.79		60.8		4.47
		123		bodo		80		CI		1528905379		66		5.91		-4.68		87.7		8.21
		124		minador do negrao		32		BR		1528905379		80		-9.31		-36.86		76.81		13.24
		125		sambava		88		MG		1528905379		100		-14.27		50.17		77.35		19.73
		126		yerbogachen		0		RU		1528905380		44		61.28		108.01		64.93		7.43
		127		kahului		1		US		1528901760		93		20.89		-156.47		66.2		3.36
		128		clyde river		75		CA		1528902660		100		70.47		-68.59		35.6		21.92
		129		ancud		20		CL		1528905381		90		-41.87		-73.83		39.1		2.73
		130		beringovskiy		0		RU		1528905381		88		63.05		179.32		39.37		3.4
		131		majene		32		ID		1528905382		100		-3.54		118.97		81.85		11.01
		132		ahar		36		IR		1528905382		62		38.48		47.07		62.77		3.74
		133		ilhabela		80		BR		1528905382		98		-23.78		-45.36		72.85		2.28
		134		listvyagi		0		RU		1528905382		78		53.68		86.95		65.11		2.06
		135		skjervoy		40		NO		1528903200		65		70.03		20.97		44.6		10.29
		136		cape town		0		ZA		1528902000		35		-33.93		18.42		73.4		9.17
		137		iqaluit		90		CA		1528902000		96		63.75		-68.52		35.6		20.8
		138		fort-shevchenko		0		KZ		1528905387		59		44.51		50.26		74.2		3.62
		139		severo-kurilsk		92		RU		1528905387		100		50.68		156.12		38.02		16.26
		140		arraial do cabo		0		BR		1528905600		65		-22.97		-42.02		80.6		4.7
		141		torbay		90		CA		1528903560		93		47.66		-52.73		50		19.46
		142		ahipara		88		NZ		1528905388		91		-35.17		173.16		56.65		9.66
		143		bandarbeyla		0		SO		1528905389		79		9.49		50.81		79.15		32.93
		144		vuktyl		92		RU		1528905389		96		63.86		57.31		52.6		7.43
		145		caravelas		0		BR		1528905390		98		-17.73		-39.27		77.62		10.45
		146		waipawa		92		NZ		1528905390		94		-39.94		176.59		50.89		9.44
		147		khomutovo		0		RU		1528905390		65		52.85		37.45		72.31		5.97
		148		acajutla		40		SV		1528901400		79		13.59		-89.83		84.2		1.12
		149		buritis		0		BR		1528905391		53		-15.62		-46.42		83.74		6.87
		150		meulaboh		48		ID		1528905392		100		4.14		96.13		82.03		3.4
		151		vaini		100		IN		1528905392		98		15.34		74.49		70.42		4.29
		152		teya		75		MX		1528901400		66		21.05		-89.07		86		13.87
		153		bambous virieux		75		MU		1528902000		69		-20.34		57.76		75.2		14.99
		154		zaragoza		20		ES		1528903800		49		41.65		-0.88		77		28.86
		155		thompson		75		CA		1528902600		76		55.74		-97.86		57.2		3.36
		156		kodiak		1		US		1528901580		50		39.95		-94.76		75.2		13.87
		157		nsanje		92		MZ		1528905397		84		-16.92		35.26		70.33		4.18
		158		the pas		1		CA		1528902000		63		53.82		-101.24		60.8		10.29
		159		masalli		12		KR		1528902000		77		34.8		126.66		68		9.17
		160		talnakh		20		RU		1528905398		100		69.49		88.39		42.79		3.18
		161		ilulissat		90		GL		1528901400		97		69.22		-51.1		32		4.7
		162		vallenar		0		CL		1528905399		56		-28.58		-70.76		54.4		1.28
		163		cap-aux-meules		40		CA		1528902000		62		47.38		-61.86		51.8		20.8
		164		san quintin		90		PH		1528902000		100		17.54		120.52		77		13.87
		165		victoria		75		BN		1528902000		94		5.28		115.24		80.6		1.12
		166		okhotsk		12		RU		1528905400		100		59.36		143.24		38.02		2.17
		167		bonavista		92		CA		1528905401		82		48.65		-53.11		46.57		22.97
		168		manokwari		80		ID		1528905401		100		-0.87		134.08		78.07		8.1
		169		lebu		92		ET		1528905404		100		8.96		38.73		55.3		0.72
		170		qostanay		75		KZ		1528902000		54		53.17		63.58		59		6.71
		171		victor harbor		75		AU		1528902000		82		-35.55		138.62		55.4		17.22
		172		kamenka		12		RU		1528905405		98		53.19		44.05		61.6		9.44
		173		cherskiy		8		RU		1528905405		48		68.75		161.3		55.21		3.18
		174		kimbe		92		PG		1528905405		100		-5.56		150.15		78.43		6.64
		175		guba		75		PH		1528902000		74		10.43		123.89		84.2		8.05
		176		inuvik		40		CA		1528902000		53		68.36		-133.71		51.8		3.36
		177		jiazi		20		CN		1528902000		78		19.61		110.49		82.4		4.47
		178		namatanai		76		PG		1528905407		100		-3.66		152.44		78.07		11.68
		179		port elizabeth		90		US		1528903500		83		39.31		-74.98		75.2		9.17
		180		chilca		75		PE		1528903800		47		-13.22		-72.34		55.4		3.

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