Create README.md

Author: ht3886

README.md

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+# Overview
+Data extraction for parks in Nova Scotia, Canada and visualization 
+
+## Dataset Source
+
+https://data.novascotia.ca/Lands-Forests-and-Wildlife/DNR-Camping-Parks-Reservation-Data-2016/4zt7-x443
+
+### About the Dataset
+
+The dataset DNR Camping Parks Reservation Data 2016 lists various camping sites in Nova Scotia and this information is collected through the reservation system 
+for the general public to reserve camping sites in Nova Scotia. The dataset has 34,900 rows and 13 columns. It lists a lot of information regarding the park’s 
+name (ParkName), origin state and country of the water body, total booking size (partySize), type of rate (RateType), the type of booking (BookingType), Equipment, 
+Booking start date along with its end date, night and their permits.
+
+## File Description
+
+### file1.csv
+
+I have used the csv module to read and write the contents from the dataset csv file named DNR_Camping_Parks_Reservation_Data_2016.csv to file1.csv respectively. 
+To create the csv file from extracting all the data from dataset, I have used the functions ‘csv.writer’ and ‘csv.reader’ to write and read data respectively. 
+As I am dealing with csv files, naturally the delimiter used is comma (,).
+
+### file2.csv
+
+Here I have removed the unnecessary columns and extracted data on ParkName, State, PartySize, BookingType, RateType and Equipment.
+
+### file3.csv
+
+Scanned the "Equipment" column, and replaced all “less than” with “LT” [e.g. less than 30 ft. after transforming LT30ft]. Similarly, replaced all “Single tent” with “ST”.
+I have used the regex module to perform this substitutions. To find and replace these words, I have used the ‘.sub’ function. I have replaced and substituted both the 
+words consecutively rather than simultaneously to make the code simpler.
+
+### file4.csv
+
+This file has only the 20 unique parks in Nova Scotia which have the maximum number of "partySize".
+
+## Visualization using Neo4j
+
+### Load data and node creation
+![](graph%20images/load_data_and_node_creation.png)
+
+### Parks with identical ‘RateType’, connected using a ‘NeghbourByRate’ relation
+![](graph%20images/NeghbourByRate.png)
+
+### Parks with identical ‘Equipment’, connected using a ‘NeghbourByEquipment’ relation
+![](graph%20images/NeghbourByEquipment.png)
+
+### Final Image file that has both the relations: NeghourByRate and NeghbourByEquipment
+![](graph%20images/graph.png)
+
+### Using visualization, found the park with maximum "partySize"
+![](graph%20images/visualization.png)
+