Adding Mexico city

Author: datapythonista

pandas/index.html

@@ -180,15 +180,15 @@
              "address": "TBC",
              "lat": 19.076004,
              "lng": 72.877371},
-	    {"title": "Kanpur",
-	     "description": "PyData Kanpur",
-	     "url": "https://www.meetup.com/PyDataKanpur/events/248266945/",
+            {"title": "Kanpur",
+             "description": "PyData Kanpur",
+             "url": "https://www.meetup.com/PyDataKanpur/events/248266945/",
              "sponsor_image": "",
              "sponsor_url": "",
-             "time" : "1 pm",
-	     "address": "Allies Interactive<br/> The Mall",
-	     "lat": 26.4672319,
-	     "lng": 80.3600952},
+             "time" : "1pm",
+             "address": "Allies Interactive<br/>The Mall",
+             "lat": 26.4672319,
+             "lng": 80.3600952},
 
             // Americas
             {"title": "Seattle",
@@ -254,7 +254,7 @@
              "address": "TBC",
              "lat": -19.919126,
              "lng": -43.938628},
-             {"title": "Brasília",
+            {"title": "Brasília",
              "description": "PyData Brasília",
              "url": "https://www.meetup.com/PyData-Brasilia/",
              "sponsor_image": "",
@@ -263,6 +263,15 @@
              "address": "TBC",
              "lat": -15.793962,
              "lng": -47.882927},
+            {"title": "Mexico City",
+             "description": "Mexico City",
+             "url": "#",
+             "sponsor_image": "",
+             "sponsor_url": "",
+             "time": "TBC",
+             "address": "TBC",
+             "lat": 19.432626,
+             "lng": -99.133203},
 
 
             // Africa