Visualising data for @photocontests - week 16/04/18-22/04/18

🔗 click on visuals for full screen view

📉 `1616` Participants all Week

#tag	Number of Posts	Number of Participants	Weekly Changes, %
#foodphotography	544	479	`+7.1 %`
#animalphotography	614	547	`+12.7%`
#landscapephotography	299	256	`+0.7 %`
#cityscapephotography	139	131	-11.5 %
#architecturalphotography	189	177	`+1.6 %`
#vehiclephotography	162	155	`+7.3 %`
#macrophotography	278	243	`+124.2 %`
#colourfulphotography	224	195	`+160.5 %`
#streetphotography	260	234	-6.1 %
#portraitphotography	167	146	-16.9 %
#sportsphotography	79	78	-1.3 %
#smartphonephotography	663	462	-11.4 %
#goldenhourphotography	285	262	`+10.9 %`
#longexposurephotography	85	81	-2.3 %

Day of the week	Participants in both contests
Monday	134
Tuesday	50
Wednesday	54
Thursday	61
Friday	43
Saturday	22
Sunday	36

Author	Number of Posts	Author	Number of Posts
@sajji	36	@shaifullah	12
@cetuna	31	@olega-friend777	12
@stewsak	20	@mojacko	12
@xroni	19	@camuel	12
@batatzone	15	@sketch17	11
@axeman	15	@usmn	11
@mur	14	@fortunee	11
@adipa	13	@katekor11	11
@yurche	12	@che-nie	11
@sinta2	12	@vinceboisgard	11

💪💪💪 @batatzone

The data represents the CET (UTC+1), which is the official time for @photocontests!

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Sunday

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.