❗️ Sorry, a little bit late this time with the stats.
🔗 click on visuals for full screen view
2️⃣0️⃣4️⃣6️⃣ Unique Participants all Week
4️⃣7️⃣4️⃣1️⃣ Entries all Week
Number of Posts and Participants per Tag
| Number of Posts | Number of Participants | Weekly Changes, % | |
|---|---|---|---|
| #foodphotography | |||
| #animalphotography | |||
| #landscapephotography | |||
| #cityscapephotography | |||
| #architecturalphotography | |||
| #vehiclephotography | |||
| #macrophotography | |||
| #colourfulphotography | |||
| #streetphotography | |||
| #portraitphotography | |||
| #sportsphotography | |||
| #smartphonephotography | +9.1 % | ||
| #goldenhourphotography | +27.6 % | ||
| #longexposurephotography | +23.5 % |
Number taking part in both Contests of the Day
Number of Participants each Day
| Weekly Changes, % | ||
|---|---|---|
+10.6 % | ||
+22.9 % |
Histogram of Number of Posts every 15 minutes
The data represents the CET (UTC+1), which is the official time for 
Background Info
I have extracted the data using api.steemit.com and the following api call:
payload = '{"id":4,"jsonrpc":"2.0","method":"call","params":["database_api","get_discussions_by_created", [{"tag":"' + tag + '","limit":100}]]}'
I am using pandas library. Pandas is an open source and is designed for Python users for data analysis and manipulation.
Monday: foodphotography and animalphotography
Tuesday: landscapephotography and cityscapephotography
Wednesday: architecturalphotography and vehiclephotography
Thursday: macrophotography and colourfulphotography
Friday: streetphotography and portraitphotography
Saturday: sportsphotography and smartphonephotography
Sunday: goldenhourphotography and longexposurephotography