Data Exploration


This page explores patterns and justifies directions for modeling within the cleaned data. The following Python scripts were used to create the visualizations:



Given over 5 years of recent weather data observations from mountainous areas near ski resorts, this boxplot can reveal the spread of different numeric weather variables. Even though these variables are not in the same units, it does present patterns and raise questions. Ulimately, this helps guide the analysis into finding relationships between variables.

Summary of over 5 years of weather data in mountainous areas.

Averaging across all resorts and over five years, this indicates that the major ski resort pass companies could potentially favor resorts which receive more snow. This is especially telling since the majority of the resorts in this analysis are not Epic nor Ikon.


Average annual snow by pass type.

The western United States up into central Canada receive, on average, more snow than other major geographical regions in North America. These regions include mountain ranges such as Sierra Nevada, the Cascades, and the Rockies.


Average annual snow by major North American region.

The The National Snow and Ice Data Center (NSIDC) stated that low temperatures and moisture in the air (humidity) are required for snow to form. Is that effect apparent in the data? Does vary across the major North American regions? It appears there is a correlation!


Effect of Humidity and Temperature on Snow by Major North American regions.

The United States boasts the highest number of ski resort visitors of any single country. Given the United States' proximity to Canada, do ski resorts still hold a higher ratings than Canada? Overall, the Untied States' interquartile range dwarfs much of Canada's resort ratings. Canada does have a few outliers with higher ratings, however, they are still within the normal range of data for the United States' ratings.


Spread of overall resort ratings by country.

The average snowfall on Epic and Ikon pass resorts were undeniably higher than for resorts with other passes. The spread of resort ratings for Epic and Ikon passes are higher than the resorts with other passes. Interestingly, the spread of Ikon is much smaller than that of Epic but with a concentration towards higher ratings. It might be a decent angle to examine if snowfall is correlated with higher resort ratings.


Resort ratings by pass type.

Following from the previous line of inquiry about snow amount to resort rating, it does appear that the West and West Coast regions, which were also the top per country in the amount of snowfall do contain the higher ratings as well. This is further evidence that snowfall may be correlated with resort rating.


Resort ratings by major North American region.

Given there is some evidence that more snowfall could increase a resort's rating, do resorts with a higher rating charge more for skiers and snowboards to use their mountains? There is a linear trend present that resorts with higher ratings do charge more, with the United States seemingly charging more for similarly rated resorts.


Does rating affect price?

Given the spread of snowfall and resort ratings across the major regions within North America, will ratings for businesses near ski resorts follow suit? Aside from the medical category ratings, it does appear that the United States might have higher rated businesses across most categories. Whether or not that is statistically significant is difficult to gather across most the images in this chart. However, it does appear that the North region in Canada is an outlier on the lower end throughout these ratings.


Categorical ratings of businesses near ski resorts by major North American region.

What actually contributes heavily towards a resort's rating? The resort dataset itself features a few variables which are rating specific. Those being individual ratings on Lifts Quality, Run Variety, Resort Size, and Overall Rating. It appears that Run Variety, Resort Size, and Overall Rating have the greatest effects on each other.


Correlations Between Resort Ratings

Expanding out the correlation matrix to account for all of the numerical variables with the dataset, different patterns start to emerge. There aren't too many surprises from this visual, but it can help to confirm where correlations are strongest and weakest.


Correlations Between Resort Numerical Variables

Finally, by taking all numerical variables from all three of the main datasets (Resorts, Weather, and Google Places), a roadmap between new associations can be illuminated. This could have applications in feature reduction and model efficiency. See below the image for a table version of the results.


Total Numeric Correlation Heatmap

Overall Rating Elevation Difference Elevation Low Elevation High Trails Total Trails Easy Trails Intermediate Trails Difficult Lifts Price Resort Size Run Variety Lifts Quality Latitude Longitude rating_bars rating_grocery rating_lodging rating_medical rating_restaurants rating_shopping rating_spas tempmax tempmin temp feelslikemax feelslikemin feelslike dew humidity precip precipcover snow snowdepth windgust windspeed winddir pressure cloudcover visibility solarradiation solarenergy uvindex
1.000000 0.878455 0.533330 0.687645 0.877542 0.774813 0.854863 0.797437 0.711891 0.867831 0.922904 0.955462 0.756211 -0.159087 -0.323852 0.044878 0.038096 0.086869 -0.059538 -0.032403 0.016687 0.057089 0.029445 -0.145323 -0.073714 0.027188 -0.132998 -0.055101 -0.348755 -0.372850 -0.282842 -0.105041 0.501251 0.364358 0.329537 0.030381 0.067835 0.373365 -0.228627 -0.035070 0.273776 0.273112 0.311668
0.878455 1.000000 0.567666 0.751151 0.843513 0.726144 0.818881 0.778953 0.631959 0.824755 0.882894 0.901982 0.631363 -0.103724 -0.411456 -0.003369 0.001832 0.119277 -0.067613 -0.007133 0.016446 0.023636 0.035291 -0.180356 -0.091404 0.036113 -0.159857 -0.064716 -0.379753 -0.384427 -0.309415 -0.147735 0.506205 0.388784 0.316782 0.042803 0.053466 0.362499 -0.246494 -0.070624 0.303856 0.303073 0.324660
0.533330 0.567666 1.000000 0.969861 0.558410 0.466565 0.537394 0.527698 0.408766 0.597069 0.571936 0.593801 0.329592 -0.414861 -0.644025 -0.046840 0.023958 -0.014063 -0.133881 -0.020548 0.070160 0.011459 0.290703 -0.092061 0.095112 0.244069 -0.111346 0.074294 -0.586435 -0.860443 -0.629944 -0.502398 0.456745 0.425263 0.572574 0.360973 0.162654 0.608281 -0.678271 -0.146480 0.651160 0.650379 0.698041
0.687645 0.751151 0.969861 1.000000 0.697414 0.589031 0.673272 0.653680 0.514808 0.722861 0.719915 0.743097 0.451146 -0.363355 -0.638189 -0.037516 0.019233 0.024229 -0.124971 -0.018474 0.060052 0.016329 0.243545 -0.127199 0.049213 0.206395 -0.136595 0.040418 -0.582628 -0.803724 -0.596698 -0.446573 0.516061 0.456064 0.552876 0.302114 0.146249 0.595039 -0.616826 -0.138357 0.612064 0.611206 0.655813
0.877542 0.843513 0.558410 0.697414 1.000000 0.844172 0.956559 0.946406 0.807338 0.845323 0.912782 0.880317 0.577842 -0.172446 -0.351949 0.036285 -0.014664 0.107034 -0.096763 -0.022895 0.019980 0.026637 0.015266 -0.177127 -0.097319 0.005240 -0.177809 -0.089416 -0.385173 -0.397470 -0.345973 -0.162107 0.485785 0.340788 0.360829 0.125142 0.088602 0.415504 -0.259811 -0.055688 0.300560 0.299803 0.349038
0.774813 0.726144 0.466565 0.589031 0.844172 1.000000 0.751420 0.707592 0.690526 0.728340 0.827346 0.796502 0.520137 -0.150133 -0.278034 0.021721 -0.014782 0.085274 -0.074853 -0.053149 -0.026137 0.020786 0.001798 -0.189415 -0.104839 -0.005227 -0.171490 -0.090135 -0.324193 -0.310225 -0.276086 -0.109952 0.449682 0.297649 0.307970 0.075524 0.111875 0.390812 -0.209585 -0.064935 0.210274 0.209516 0.262702
0.854863 0.818881 0.537394 0.673272 0.956559 0.751420 1.000000 0.848454 0.786499 0.830872 0.888671 0.838358 0.583689 -0.174452 -0.357051 0.053767 0.007958 0.124482 -0.112847 0.010576 0.044977 0.046619 0.046136 -0.141798 -0.061904 0.040302 -0.133975 -0.047890 -0.353600 -0.395204 -0.321652 -0.151875 0.484629 0.323597 0.323255 0.079869 0.039912 0.394314 -0.263813 -0.050220 0.290978 0.290238 0.342176
0.797437 0.778953 0.527698 0.653680 0.946406 0.707592 0.848454 1.000000 0.745091 0.769979 0.818962 0.809426 0.499027 -0.151283 -0.322341 0.019478 -0.035127 0.081576 -0.075023 -0.037054 0.014726 0.004776 -0.011641 -0.174972 -0.111876 -0.025657 -0.193682 -0.115039 -0.379988 -0.374066 -0.345022 -0.170475 0.419262 0.319802 0.361838 0.174102 0.109985 0.375790 -0.235483 -0.046555 0.303310 0.302669 0.338401
0.711891 0.631959 0.408766 0.514808 0.807338 0.690526 0.786499 0.745091 1.000000 0.793950 0.727418 0.670254 0.532523 -0.311235 -0.213627 0.069575 -0.008751 0.112824 -0.192713 -0.022715 0.013861 0.046685 0.108630 -0.032610 0.032686 0.100571 -0.039239 0.030746 -0.213265 -0.335074 -0.218559 -0.106230 0.391841 0.241113 0.341328 0.131961 0.066227 0.444719 -0.297730 -0.185649 0.238144 0.237142 0.323114
0.867831 0.824755 0.597069 0.722861 0.845323 0.728340 0.830872 0.769979 0.793950 1.000000 0.837486 0.844430 0.690884 -0.337099 -0.346340 0.073292 0.025464 0.124572 -0.109503 -0.035547 0.017517 0.063500 0.143399 -0.065669 0.027667 0.133616 -0.066524 0.033008 -0.323829 -0.467158 -0.317563 -0.181918 0.510157 0.364742 0.419559 0.127864 0.135576 0.473039 -0.369593 -0.174714 0.373168 0.372273 0.444858
0.922904 0.882894 0.571936 0.719915 0.912782 0.827346 0.888671 0.818962 0.727418 0.837486 1.000000 0.950724 0.636164 -0.174653 -0.354616 0.012743 0.009869 0.106287 -0.117915 -0.038019 0.009708 0.049694 0.064225 -0.158707 -0.059468 0.062054 -0.134438 -0.035071 -0.365980 -0.410140 -0.314234 -0.139225 0.514692 0.374363 0.330456 0.041482 0.075308 0.391936 -0.295275 -0.066876 0.288536 0.287797 0.331879
0.955462 0.901982 0.593801 0.743097 0.880317 0.796502 0.838358 0.809426 0.670254 0.844430 0.950724 1.000000 0.641507 -0.152423 -0.376743 0.012731 0.022743 0.055890 -0.089407 -0.045877 -0.000769 0.051436 0.037366 -0.171601 -0.082780 0.031304 -0.158755 -0.065096 -0.388075 -0.412807 -0.335626 -0.158479 0.526328 0.390794 0.356233 0.072690 0.076135 0.400959 -0.265831 -0.054503 0.301062 0.300348 0.333304
0.756211 0.631363 0.329592 0.451146 0.577842 0.520137 0.583689 0.499027 0.532523 0.690884 0.636164 0.641507 1.000000 -0.234150 -0.132121 0.104148 0.046518 0.077993 -0.023238 0.020844 0.032395 0.058868 0.123985 0.035570 0.075578 0.127143 0.041743 0.085777 -0.101321 -0.228891 -0.090986 -0.006213 0.310274 0.254539 0.254319 -0.028442 0.048433 0.244903 -0.194948 -0.095868 0.198668 0.198297 0.257783
-0.159087 -0.103724 -0.414861 -0.363355 -0.172446 -0.150133 -0.174452 -0.151283 -0.311235 -0.337099 -0.174653 -0.152423 -0.234150 1.000000 -0.214447 -0.118691 -0.154463 0.002123 0.273354 -0.015717 -0.029774 -0.083493 -0.700864 -0.487641 -0.628608 -0.670816 -0.460956 -0.587894 -0.187235 0.500109 0.084262 0.146807 -0.071069 -0.032641 -0.407631 -0.179496 -0.337416 -0.544881 0.660727 0.322414 -0.436393 -0.436039 -0.641581
-0.323852 -0.411456 -0.644025 -0.638189 -0.351949 -0.278034 -0.357051 -0.322341 -0.213627 -0.346340 -0.354616 -0.376743 -0.132121 -0.214447 1.000000 0.062756 0.053889 -0.039243 -0.057595 0.013109 -0.112244 0.031049 -0.077426 0.175081 0.060638 -0.066828 0.147526 0.036996 0.478011 0.537597 0.521815 0.405943 -0.353258 -0.402117 -0.096090 -0.115241 0.235028 -0.226295 0.368345 0.026156 -0.322878 -0.322062 -0.253020
0.044878 -0.003369 -0.046840 -0.037516 0.036285 0.021721 0.053767 0.019478 0.069575 0.073292 0.012743 0.012731 0.104148 -0.118691 0.062756 1.000000 -0.115053 0.137318 -0.160989 -0.039652 -0.041446 0.123816 0.133485 0.147231 0.151427 0.127494 0.132637 0.137611 0.135909 -0.014028 -0.037552 0.001016 -0.030594 -0.015073 0.058998 0.041413 0.107524 0.002451 -0.055624 -0.081634 0.037762 0.038114 0.064690
0.038096 0.001832 0.023958 0.019233 -0.014664 -0.014782 0.007958 -0.035127 -0.008751 0.025464 0.009869 0.022743 0.046518 -0.154463 0.053889 -0.115053 1.000000 0.040712 -0.065284 0.019280 0.085209 0.072740 0.134198 0.094262 0.122316 0.137356 0.101263 0.126435 0.043757 -0.108418 0.018081 -0.048759 -0.027733 0.066122 0.002912 -0.038773 0.063412 0.074430 -0.137364 -0.073421 -0.025662 -0.025453 0.045339
0.086869 0.119277 -0.014063 0.024229 0.107034 0.085274 0.124482 0.081576 0.112824 0.124572 0.106287 0.055890 0.077993 0.002123 -0.039243 0.137318 0.040712 1.000000 0.046105 -0.058703 0.108671 0.137445 0.041916 -0.007657 0.016870 0.056372 0.026327 0.041325 0.025180 0.016525 0.011099 0.020258 -0.034157 -0.092459 -0.057482 -0.127355 -0.013610 -0.007868 -0.015174 -0.075727 -0.044188 -0.044270 -0.019899
-0.059538 -0.067613 -0.133881 -0.124971 -0.096763 -0.074853 -0.112847 -0.075023 -0.192713 -0.109503 -0.117915 -0.089407 -0.023238 0.273354 -0.057595 -0.160989 -0.065284 0.046105 1.000000 -0.044063 0.003954 -0.045242 -0.142137 -0.014029 -0.085531 -0.135309 -0.015536 -0.080529 0.057484 0.194387 0.041596 0.121090 -0.140871 -0.044059 -0.143264 -0.155119 0.008569 -0.123179 0.237758 0.206733 -0.168458 -0.167916 -0.207813
-0.032403 -0.007133 -0.020548 -0.018474 -0.022895 -0.053149 0.010576 -0.037054 -0.022715 -0.035547 -0.038019 -0.045877 0.020844 -0.015717 0.013109 -0.039652 0.019280 -0.058703 -0.044063 1.000000 0.146386 0.143717 0.034546 0.030265 0.033624 0.037965 0.032954 0.035370 0.033965 0.013444 0.040708 0.016750 -0.100902 -0.190947 -0.065471 -0.022002 0.011127 0.007527 0.011993 0.024524 -0.003344 -0.003573 0.006479
0.016687 0.016446 0.070160 0.060052 0.019980 -0.026137 0.044977 0.014726 0.013861 0.017517 0.009708 -0.000769 0.032395 -0.029774 -0.112244 -0.041446 0.085209 0.108671 0.003954 0.146386 1.000000 0.038307 0.088788 0.005091 0.048582 0.093411 0.017741 0.059059 -0.025828 -0.088887 -0.035894 -0.166433 0.005344 -0.050918 -0.067389 -0.009631 -0.043133 0.029369 -0.113249 -0.006533 0.054291 0.054040 0.053506
0.057089 0.023636 0.011459 0.016329 0.026637 0.020786 0.046619 0.004776 0.046685 0.063500 0.049694 0.051436 0.058868 -0.083493 0.031049 0.123816 0.072740 0.137445 -0.045242 0.143717 0.038307 1.000000 0.044872 0.079933 0.066362 0.041009 0.063695 0.055528 0.027010 -0.051178 -0.040084 0.048796 0.004916 0.003798 0.030853 0.017590 0.071658 0.039648 -0.031922 -0.038348 0.024453 0.024173 0.010570
0.029445 0.035291 0.290703 0.243545 0.015266 0.001798 0.046136 -0.011641 0.108630 0.143399 0.064225 0.037366 0.123985 -0.700864 -0.077426 0.133485 0.134198 0.041916 -0.142137 0.034546 0.088788 0.044872 1.000000 0.794326 0.951219 0.994148 0.829353 0.950906 0.478311 -0.484291 -0.079096 -0.159367 -0.104067 0.022960 0.010876 -0.131833 0.040283 0.226494 -0.607529 -0.228142 0.263214 0.262827 0.428075
-0.145323 -0.180356 -0.092061 -0.127199 -0.177127 -0.189415 -0.141798 -0.174972 -0.032610 -0.065669 -0.158707 -0.171601 0.035570 -0.487641 0.175081 0.147231 0.094262 -0.007657 -0.014029 0.030265 0.005091 0.079933 0.794326 1.000000 0.940769 0.800177 0.975852 0.916178 0.783545 -0.099256 0.229368 0.182518 -0.298220 -0.126246 -0.110070 -0.183253 -0.027687 0.024980 -0.194722 -0.156035 -0.037923 -0.038167 0.103561
-0.073714 -0.091404 0.095112 0.049213 -0.097319 -0.104839 -0.061904 -0.111876 0.032686 0.027667 -0.059468 -0.082780 0.075578 -0.628608 0.060638 0.151427 0.122316 0.016870 -0.085531 0.033624 0.048582 0.066362 0.951219 0.940769 1.000000 0.950981 0.950488 0.987878 0.666066 -0.308541 0.076484 0.005750 -0.216096 -0.059257 -0.063262 -0.170738 0.002034 0.120276 -0.430242 -0.202830 0.115020 0.114715 0.278357
0.027188 0.036113 0.244069 0.206395 0.005240 -0.005227 0.040302 -0.025657 0.100571 0.133616 0.062054 0.031304 0.127143 -0.670816 -0.066828 0.127494 0.137356 0.056372 -0.135309 0.037965 0.093411 0.041009 0.994148 0.800177 0.950981 1.000000 0.850833 0.964740 0.518629 -0.431741 -0.029750 -0.117144 -0.115353 0.004352 -0.056828 -0.215438 0.013411 0.201915 -0.567610 -0.222273 0.211558 0.211157 0.376430
-0.132998 -0.159857 -0.111346 -0.136595 -0.177809 -0.171490 -0.133975 -0.193682 -0.039239 -0.066524 -0.134438 -0.158755 0.041743 -0.460956 0.147526 0.132637 0.101263 0.026327 -0.015536 0.032954 0.017741 0.063695 0.829353 0.975852 0.950488 0.850833 1.000000 0.957739 0.801996 -0.077096 0.254436 0.203297 -0.283678 -0.120177 -0.223876 -0.350364 -0.074551 -0.009066 -0.194599 -0.142278 -0.079770 -0.079993 0.063046
-0.055101 -0.064716 0.074294 0.040418 -0.089416 -0.090135 -0.047890 -0.115039 0.030746 0.033008 -0.035071 -0.065096 0.085777 -0.587894 0.036996 0.137611 0.126435 0.041325 -0.080529 0.035370 0.059059 0.055528 0.950906 0.916178 0.987878 0.964740 0.957739 1.000000 0.676555 -0.275669 0.107752 0.036530 -0.202212 -0.055081 -0.149046 -0.296544 -0.039190 0.093894 -0.406537 -0.187216 0.072441 0.072123 0.232806
-0.348755 -0.379753 -0.586435 -0.582628 -0.385173 -0.324193 -0.353600 -0.379988 -0.213265 -0.323829 -0.365980 -0.388075 -0.101321 -0.187235 0.478011 0.135909 0.043757 0.025180 0.057484 0.033965 -0.025828 0.027010 0.478311 0.783545 0.666066 0.518629 0.801996 0.676555 1.000000 0.495618 0.574177 0.469277 -0.432147 -0.307624 -0.407292 -0.410659 -0.091770 -0.211737 0.231063 -0.059507 -0.408513 -0.408275 -0.314828
-0.372850 -0.384427 -0.860443 -0.803724 -0.397470 -0.310225 -0.395204 -0.374066 -0.335074 -0.467158 -0.410140 -0.412807 -0.228891 0.500109 0.537597 -0.014028 -0.108418 0.016525 0.194387 0.013444 -0.088887 -0.051178 -0.484291 -0.099256 -0.308541 -0.431741 -0.077096 -0.275669 0.495618 1.000000 0.653466 0.587446 -0.303352 -0.325805 -0.483513 -0.361935 -0.155826 -0.449084 0.796416 0.180606 -0.653674 -0.652981 -0.728825
-0.282842 -0.309415 -0.629944 -0.596698 -0.345973 -0.276086 -0.321652 -0.345022 -0.218559 -0.317563 -0.314234 -0.335626 -0.090986 0.084262 0.521815 -0.037552 0.018081 0.011099 0.041596 0.040708 -0.035894 -0.040084 -0.079096 0.229368 0.076484 -0.029750 0.254436 0.107752 0.574177 0.653466 1.000000 0.737222 -0.131038 -0.170042 -0.296124 -0.392903 -0.140227 -0.318694 0.478463 0.043001 -0.490055 -0.489881 -0.465568
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