# data[].attributes.body
It went up to 15 then across to 20 then up to 40

# data[].attributes.body
It started in Jan at 9, went down to 8.4 in Feb then went across at a downwards angle to Mar at 8.3 then went down and across at an angle to may at 7.5 then went downwards at an angle to Jun at 7.2 then went across at a downward angle to Jul at 7.1 and that's when it begins to go up to Aug at 7.9 then went straight up at an angle to Oct 8.9 then went up at an angle to Nov at 9.8 and finally it went straight up at an angle to Dec at 12.1

# data[].attributes.body
So, the water began to go down at the start of the day "12am" at a slow downward angle until 6am in the morning then it picks up the pace as it goes down to 9am then Noon and heads straight down at a downward angle to 3pm as it curved to 6pm then continued its path to 9pm and finally 12pm.

# data[].attributes.body
it went up very high

# data[].attributes.headline
it dropped in July and then increased quickly in November  

# data[].attributes.subject
it dropped in July and then increased quickly in November  

# data[].attributes.body
the water remained high at 12am and dropped down around 6am and continued to decline till 3pm where it stayed low until around 11-12am.

# data[].attributes.body
it was travelling 1.5km per 15 mins then sat at 1.5km for 5 mins. It then continued to travel and took 20 mins to shoot up to 3 kms at the 40 min mark.

# data[].attributes.body
The price started at $8.90 in January, it then went down to $8.30 in March, then in May the price was down at $7.50, it continued to drop to $7.20 in July. During July the price started to ascend, getting to $8 in September, then in November $10, and eventually got to $12 in December.

# data[].attributes.body
It went up to 1.5km in 15 mins then stayed there for another 5 the quickly increased.

# data[].attributes.body
Slowly decreased till July then quickly increased and kept increasing

# data[].attributes.body
the water dropped at 9am till 3:30 then stayed at around the same for the rest of the day

# data[].attributes.body
share prices dropped by two, leading into July then in July share prices rocketed up by 4.5 flowing into November

# data[].attributes.body
stocks went up by 15 in 10 mins stock shot up to 40

# data[].attributes.body
The water started to decrease slowly at 12 AM until 6 AM. It then dropped more sharply until 9 AM, continued at a steady pace to noon, and steepened until 3 PM, curving down to 6 PM, before maintaining a downward trend until 9 PM and finally midnight.

# data[].attributes.body
the trend of this graph was a steady incline of 1.5km per 15 minutes, then it came to a halt for 5 minutes, before it steadily inclined again up to 40 minutes

# data[].attributes.body
This graph is telling you that the race was increasing at a steady pace until the 15 min mark, where the km stood still until the 20 min mark, then it continued to increase at a steady pace .

# data[].attributes.body
January the share price was $9 then the share price decreased to $7in july then increased to $12 in nov

# data[].attributes.body
It went to steadily up to 15 then stay to 20 and took a leap to 40

# data[].attributes.headline
the time and distance increased together

# data[].attributes.subject
the time and distance increased together

# data[].attributes.body
The time and distance both increased

# data[].attributes.body
it went up

# data[].attributes.body
It traveled 1.5km for 15 minutes, then it sat at 1.5km for 5 minutes. It travelled up to 3km, taking 20 minutes to reach the 40 minute mark.

# data[].attributes.body
it got 1.5km in 15 minutes stayed for minutes then quickly increased. Takes around 22 minutes to get 2km

# data[].attributes.body
started in January at 9 then decreased til July. February 8.4 March 8.3 April 7,5 July 7.1 then increases quickly in september 8 November 9.8 December 12

# data[].attributes.body
The trend is increasing, then it stays steady and begins to increase again

# data[].attributes.body
Then trend quickly decrease but then steadied before rapidly increasing

# data[].attributes.body
there was a slow decrease until rates rapidly decreased then steadily decreases and continues fairly evenly