@@ -18,3 +18,15 @@
 ![faircoopDataAnalytics](https://raw.githubusercontent.com/arnaucode/faircoopDataAnalytics/master/chartsResults/fairmarket-products02.png "faircoopDataAnalytics")
 
 ![faircoopDataAnalytics](https://raw.githubusercontent.com/arnaucode/faircoopDataAnalytics/master/chartsResults/fairmarket-products03.png "faircoopDataAnalytics")
+
+#### BotC
+
+Members
+
+![faircoopDataAnalytics](https://raw.githubusercontent.com/arnaucode/faircoopDataAnalytics/master/chartsResults/botc-members01.png "faircoopDataAnalytics")
+
+![faircoopDataAnalytics](https://raw.githubusercontent.com/arnaucode/faircoopDataAnalytics/master/chartsResults/botc-members02.png "faircoopDataAnalytics")
+
+![faircoopDataAnalytics](https://raw.githubusercontent.com/arnaucode/faircoopDataAnalytics/master/chartsResults/botc-members03.png "faircoopDataAnalytics")
+
+![faircoopDataAnalytics](https://raw.githubusercontent.com/arnaucode/faircoopDataAnalytics/master/chartsResults/botc-members04.png "faircoopDataAnalytics")

@@ -0,0 +1,77 @@
+# coding=utf-8
+import sys
+reload(sys)
+sys.setdefaultencoding('utf8')
+
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from datetime import datetime, date, timedelta
+
+members = pd.read_csv('datasets/BotC.csv')
+
+print members.head(1)
+
+#generate the full set of days from the first date to the last in the dataset
+months = []
+days = []
+dInit = date(2017, 6, 8)
+dEnd = date(2017, 1, 9)
+delta = dEnd - dInit
+for i in range(delta.days+1):
+    day = dInit + timedelta(days=i)
+    dayString = day.strftime("%d/%m/%y")
+    dayDatetime = datetime.strptime(dayString, '%d/%m/%y')
+    days.append(dayDatetime)
+
+#add the dates of shops creation to the days array
+for memberDate in members['Date']:
+    if isinstance(memberDate, basestring):
+        memberDay = memberDate
+        memberDayDatetime = datetime.strptime(memberDay, '%B %d, %Y')
+        days.append(memberDayDatetime)
+
+#count days frequency in days array
+unique, counts = np.unique(days, return_counts=True)
+countDays = dict(zip(unique, counts))
+realCounts = []
+for count in counts:
+    realCounts.append(count-1)
+
+#count the total acumulation of shops created in each days
+totalCount = 0
+globalCount = []
+for k in realCounts:
+    totalCount = totalCount + k
+    globalCount.append(totalCount)
+
+dates = countDays.values()
+counts = countDays.values()
+
+#plot the data
+plt.title("New members registered each day")
+plt.plot(unique, realCounts)
+plt.show()
+
+plt.title("Total members each day")
+plt.plot(unique, globalCount)
+plt.show()
+
+plt.title("New members and total members each day")
+plt.plot(unique, realCounts, label="new members registered each day")
+plt.plot(unique, globalCount, label="total members each day")
+plt.legend(loc='upper left')
+plt.show()
+
+
+# place of the account
+places = []
+for place in members["Place"]:
+    if isinstance(place, basestring):
+        places.append(place)
+
+placesNames, placesCount = np.unique(places, return_counts=True)
+plt.title("Membership places")
+plt.pie(placesCount, labels=placesNames, autopct='%1.1f%%', shadow=True, startangle=90)
+plt.axis('equal')
+plt.show()

@@ -1,11 +1,20 @@
+# coding=utf-8
+import sys
+reload(sys)
+sys.setdefaultencoding('utf8')
+
 import numpy as np
 import pandas as pd
 import matplotlib.pyplot as plt
+
+import mpld3
+from mpld3 import plugins, utils
+
 from datetime import datetime, date, timedelta
 
 products = pd.read_csv('datasets/fairMarket-products.csv')
 
-print products.tail(1)
+#print products.tail(1)
 
 #generate the full set of days from the first date to the last in the dataset
 months = []
@@ -57,3 +66,18 @@ plt.plot(unique, realCounts, label="new products offered each day")
 plt.plot(unique, globalCount, label="total products in FairMarket each day")
 plt.legend(loc='upper left')
 plt.show()
+
+
+
+
+# now, product categories analytics
+categories = []
+for category in products["Categoría pública/Display Name"]:
+    if isinstance(category, basestring):
+        categories.append(category)
+
+categoriesNames, categoriesCount = np.unique(categories, return_counts=True)
+plt.title("Products categories")
+plt.pie(categoriesCount, labels=categoriesNames, autopct='%1.1f%%', shadow=True, startangle=90)
+plt.axis('equal')
+mpld3.show()

@@ -1,3 +1,8 @@
+# coding=utf-8
+import sys
+reload(sys)
+sys.setdefaultencoding('utf8')
+
 import numpy as np
 import pandas as pd
 import matplotlib.pyplot as plt