The table below shows the table made by a coffee shop in an office building on a typical weekday. Summarize the information by selecting and reporting the main features, and make comparisons where relevant. You should write at least 150 words.

The table below shows the table made by a coffee shop in an office building on a typical weekday.

Summarize the information by selecting and reporting the main features, and make comparisons where relevant. 

You should write at least 150 words.
The table illustrates the orders of
coffee
,
tea
, pastries and
sandwiches
in an office on a common weekday.
Overall
,
coffee
was the most popular for most of the periods of
time
while
the
order
of
tea
was relatively fewer. Pasteries were ordered most in earlier
time
and
sandwiches
were mostly eaten around noon. Starting with the graph of
coffee
and
tea
,
coffee
seemed to be ordered most for most of the examined
time
. The number of
order
Fix the agreement mistake
orders
show examples
was the highest at 265 from 7:30 to 10:30.
Although
it gradually declined as the
time
went by, dropping to 185 from 10:30 to 2:30 and 145 from 2:30 to 5:30, the
order
increased again to 200 by the
last
three hours.
In contrast
, the number of
tea
purchased by customers remained comparatively smaller, especially the
time
between 2:30 and 5:30 when only 35
order
was made.
However
,
tea
was mostly ordered with 110 from 7:30 and 10:30. Turing to the chart for pastries and
sandwiches
, there were the most orders of pastries with 275 from 7:30 to 10:30, followed by 150 between 2:30 and 5:30. The least number of
order
was made from 5:30 to 8:30 with 80.
Sandwiches
were mostly bought from 10:30 to 2:30 when 200
order
was made, which was almost twice as much as that between 5:30 and 8:30. They were much less popular between 7:30 and 10:30, 2:30 and 5:30 at 50 or less.
Submitted by mizuho on

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Vocabulary: Replace the words coffee, tea, sandwiches, time, order with synonyms.
Vocabulary: The word "number of" was used 3 times.

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Topic Vocabulary:
  • peak hours
  • typical weekday
  • busiest period
  • least busy period
  • sales volume
  • time intervals
  • items sold
  • employee preferences
  • observable patterns
  • anomalies
  • trends
  • dips
  • spikes
  • data analysis
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