This analysis provides measurable outcomes for each category/subcategory specified by location. The following are what have been analyzed further.
*The US market has been analyzed further to show the failed campaigns have a higher goal expectation but minimal interest from backers.
*The top 5 plays are successful with the goal expectations.
-* A stacked chart provided to show the outcomes of each categories 
*Similar chart provided for subcategories
*Line chart provided to show trends throughout year for parent categories 
Reccommendations are to continue with the successful campaigns however revisit the failed campaigns and setting a more realistic goal for each.
Louise, a new playwrite requires funding for her new play, Fever. She needs to start a crowdfunding campaign to help fund her play, which has a budget of $10,000. However she requires assistance in understanding how to kickstart her funding campaign to ensure a succesful turnaround.
This would help her to determine if there is a trend for better funding goals based on time frames. She will also be able to quantify how succesful, failed and canceled campaigns are and if goal factors correlate to the outcome of the campaigns.
From the large data set, a separate chart was created with launch dates for only the successful, failed and canceled campaigns. Live campaigns would not be valid as they are still active in receiving funds. This chart helps quantify total for each outcomes and popularity in the time of year. Total campaigns launched and ended were 1369. Out of that 839 were successful, 493 failed and 37 were canceled.
Thus far, successful campaigns peak in May, June and July with 10%-13% higher than the other months. Successful campaigns amount to 61% of total campaigns launched and ended. Failed campaigns amount to 36% of total campaigns launched. Canceled campaigns at a minimal of 3%.
A line chart included helps visualize the peak and downward trend.
A table was created for an isolated analysis of goals set for each campaign. Each successful, failed and canceled campaign were categorized in ranges to tabulate totals. Each range increases by 4999. This helps in understanding what goal range is more successful. Currently 76% of the total projects were successful with goals $1000 or less. The second range of $1000 to $4999 has a successful rate of 73%. With goals between $5000 to $19999, there is an average of 53% chance of being successful and an average of 47% failing. The outlier is of goals more than $45000 which are more likely to fail. A line chart has been added for better visualization.
Only challenge faced was when creating pivort tables and trying to identify which selections is better suited for rows and columns for a clean tidy data.
After reviewing the data, it seems campaigns have a better success rate in the warmer months of the year. From April to Aug, the average number of total campaigns launched were 138 with an average of 88 successful campaigns. No matter the total or the time of year, approximately half of the campaigns are bound to fail. Goals set no higher than $10000, have a better success rate. So it is safe to assume Louise's play with a budget of $10000 would have a positive outcome. The higher the goal, the risk of a failed campaign increases. More data could have been provided in this data set. In order to make a more definitive analysis, there are more factors to be taken into consideration; such as marketing, reasons why campaigns were canceled and if there are other reasons factoring to the failure of a campaign. We could create a table to see if plays have a higher success rate based on country. Are goal ranges different for each location. Additionaly the currency noted would be valued differently, so would that change the goal ranges completely for each country if the conversion was done.