Update README.md

README.md

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 # NYC Bike Sharing Analysis
 ## Overview of the Analysis
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 The purpose of this analysis was to provide a group of shareholders an analysis of New York City ridesharing data so that they can provide a thorough proposal to investors for a bike sharing program in Des Moines, Iowa. Tableau was used to create several visualizations of a very large dataset of bike share data that includes trip location, trip duration, and rider type and gender. A story was created in Tableau that includes each of the visualizations. The story can be viewed by clicking the following link. 
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 [Link to Tableau Story](https://public.tableau.com/app/profile/jeremy6008/viz/NYCBikeSharingAnalysis_16543604046310/NYCBikeSharingAnalysis?publish=yes)
 
 Also, the visualizations can be seen in the images in the Results section below.
@@ -14,27 +16,35 @@ Also, the visualizations can be seen in the images in the Results section below.
 
 
 ## Results
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 Please see the visualizations and their explanations below.
 
-![Checkout_Times_for_Users.png](https://github.com/JeremyKRay/Bikesharing/blob/0352af55609d7644b92d8ddf0d2cab7f9b7d0a10/Images/Checkout%20Times%20for%20Users.png)
+![Image Link](https://github.com/JeremyKRay/Bikesharing/blob/0352af55609d7644b92d8ddf0d2cab7f9b7d0a10/Images/Checkout%20Times%20for%20Users.png)
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 This visualization shows that the vast majority of bikes were checked out for relatively short periods of time, less than 10 minutes, with the peak around 6 mins.
 
-![Checkout Times by Gender.png](https://github.com/JeremyKRay/Bikesharing/blob/0443c21ed6e9a2f6e907afc880855e4084d53979/Images/Checkout%20Times%20by%20Gender.png)
+![Image Link](https://github.com/JeremyKRay/Bikesharing/blob/0443c21ed6e9a2f6e907afc880855e4084d53979/Images/Checkout%20Times%20by%20Gender.png)
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 This visualization shows the same but that the vast majority of bikes checked out were by males.
 
-![Image Link(Gender_Breakdown.png)](https://github.com/JeremyKRay/Bikesharing/blob/ea4bed2c05b52f71061f3f7db95e98c5781aa303/Images/Gender%20Breakdown.png)
+![Image Link](https://github.com/JeremyKRay/Bikesharing/blob/ea4bed2c05b52f71061f3f7db95e98c5781aa303/Images/Gender%20Breakdown.png)
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 This pie chart confirms that the vast majority of bike share users are male.
 
-![Image Link(Trips by Weekday per Hour.png).](https://github.com/JeremyKRay/Bikesharing/blob/6077865be8c9dd2a16582cd6cb5ecf4299b81012/Images/Trips%20by%20Weekday%20per%20Hour.png)
+![Image Link](https://github.com/JeremyKRay/Bikesharing/blob/6077865be8c9dd2a16582cd6cb5ecf4299b81012/Images/Trips%20by%20Weekday%20per%20Hour.png)
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 This heat map shows that the majority of trips are taken during peak commute hours, to and from work, 6-9 am and 4-7 pm.
 
-![Image Link(Trips_by_Gender (Weekday by Hour).png).](https://github.com/JeremyKRay/Bikesharing/blob/c0cf33b5d52a7f0fab740cc102688385b78d8145/Images/Trips%20by%20Gender%20(Weekday%20by%20Hour).png)
+![Image Link](https://github.com/JeremyKRay/Bikesharing/blob/c0cf33b5d52a7f0fab740cc102688385b78d8145/Images/Trips%20by%20Gender%20(Weekday%20by%20Hour).png)
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 This heat map confirms this trend, but also by gender, reiterating that males are responsible for most trips and that they occur at peak commute times.
 
-![Image Link(User Trips by Gender Weekday.png).](https://github.com/JeremyKRay/Bikesharing/blob/c2ce56c2095c61f5daedb811f8461dee5b04a5a7/Images/User%20Trips%20by%20Gender%20Weekday.png))
+![Image Link](https://github.com/JeremyKRay/Bikesharing/blob/c2ce56c2095c61f5daedb811f8461dee5b04a5a7/Images/User%20Trips%20by%20Gender%20Weekday.png)
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 This heat map shows similar information but by weekday and includes whether the bike share riders are customers or subscribers. Subscribers are responsible for most of the trips and they occur Monday/Tuesday and Thursday/Friday. 
 
-![Image Link(Top_Ending_Locations.png).](https://github.com/JeremyKRay/bikesharing/blob/main/Top%20Ending%20Locations.png)
+![Image Link](https://github.com/JeremyKRay/Bikesharing/blob/413ef267f29daeac0ac9f04c9c39c73576b1838f/Images/Top%20Ending%20Locations.png)
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 This bubble chart shows the end locations of each of the bike share trips. This is important if one also knows the land use, zoning, and demographics of the people living and working in this area of New York City. Similar analyses can be performed for Des Moines. 
 
 ## Summary