# data[].attributes.body
From English:
Resources
Population
Estimates
Additional
Part
In and any
Number
Ranging
Both around
Emo
Touch
Per cent
Compare
Location
Remainder
Issue
Explain
Spayed
Compare
Improve
Account
Funding
Down
Increasing
Around
Resaonable

Find
Developed
Ranging

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Terms
Level
Randomly

# data[].attributes.body
thousands
first step
expensive
four year
loan debt
high
trillion
credit card
debt
investment
worth
best choice
four year
path
rate
percent
half
very much
subpar
grades
four
more
push
logical
choice
many
path
upward
terms
economic
earn
wage
piece
lack of one

# data[].attributes.body
Expensive, assuming, earn, economic, few,

# data[].attributes.headline
Funding. 100000 nimbets how many. 133000 study. Population. Estimate. 10 percent. Reasonable guess.  Compare.  Population. Arpund 520000 location. Approximately two thirds.  The remainder. Added. Program. Ranging in size.  Six to 25. Schedule. Neutered.  24. Additiobal. List. Joined. As part.  Pay $45. Different. Area. Lower. More than 3p. Past two years. Couple driven.  Most pick a day. Everybody. All. Assembly. Start at 8. One after the other. Less. Surpkus revenue

# data[].attributes.subject
Funding. 100000 nimbets how many. 133000 study. Population. Estimate. 10 percent. Reasonable guess.  Compare.  Population. Arpund 520000 location. Approximately two thirds.  The remainder. Added. Program. Ranging in size.  Six to 25. Schedule. Neutered.  24. Additiobal. List. Joined. As part.  Pay $45. Different. Area. Lower. More than 3p. Past two years. Couple driven.  Most pick a day. Everybody. All. Assembly. Start at 8. One after the other. Less. Surpkus revenue

# data[].attributes.body
Tools, processing,

# data[].attributes.body
few, thousands, first, four, weight, many, debt, 1.2 trillion, little, rate, grads, few, upward, economic, worthy, percent, investment, best, all, loan

# data[].attributes.body
Knowledge

# data[].attributes.headline
Presentation,' information understanding, a little, point, impossible, preconceived, 28, 140, a while, times, normal, 32-36, sizes, small group, under 30, often, time, immediately, 10 min, now, every all, 15 minutes, amount, spectrum, in between, all, same, incorrect, every, approaches, years. Number   

# data[].attributes.subject
Presentation,' information understanding, a little, point, impossible, preconceived, 28, 140, a while, times, normal, 32-36, sizes, small group, under 30, often, time, immediately, 10 min, now, every all, 15 minutes, amount, spectrum, in between, all, same, incorrect, every, approaches, years. Number   

# data[].attributes.body
Rhythm
Tracked
Transfer
Scored
Level
Time
Higher
Points

# data[].attributes.body
Decline, substantial, cut, number, sum, plunging
Decade
Weight
Value
Substance
Funding
Economic trends
Smaller
Limiting
Funding
Defining
Measured
Challenging
Foundation
Difference
High
Many
Long

Factors
Possibility
Fine
A lot of
Different oversold
Percent
Best

# data[].attributes.headline
finances, percentage, less, time, lack of, increasing, high, reduce, economically, small, statistics, almost, debt, consumer information, balance budgets, evidence, millions, cost, essential, rates, financial literacy, spending, several years, 1/3, graduated, 5-17, type 2, better, fundamental, manage, choices, most, priority, risk, mere

# data[].attributes.subject
finances, percentage, less, time, lack of, increasing, high, reduce, economically, small, statistics, almost, debt, consumer information, balance budgets, evidence, millions, cost, essential, rates, financial literacy, spending, several years, 1/3, graduated, 5-17, type 2, better, fundamental, manage, choices, most, priority, risk, mere

# data[].attributes.body
Times, 10-15
Periodic
Exponents
Dozen.
Tools

# data[].attributes.body
Endowment
Surge
Common
Exceed
Route
Poverty
Degrees
Address
Salary

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Growth rate

# data[].attributes.body
Presentation
Understanding
Various approaches
Write down on paper
Preconceived
Openly discuss our thoughts
Learns differently

# data[].attributes.body
Rates, percent, return, drop, sample, similar, failure, product, earning, quality, optimizing, tangible, increasing, data analysis, high, revenues, grants, demographic, find, forecast, cost, risk, erosion, change, equal, decrees, degree, reversal, average, match, data driven interventions, finish, back, long term, predictive, largest, portion, salary, charge, scarce, three-quarters, erosion, coin, reflect,

# data[].attributes.headline
contribute, age, frequently, grow, code, optional, drawing, wanes, data, position, too, percent, tech career, range spacious, quarter, field, years, physics, young, part 14, 25, 39, capacity, fastest, easiest, long-term, changing, reflect, lots, among, often, like, still, technology, generation, engineering, computer, scientist, non-profit, telecommunications, couple, decades, fewer, biggest, doctor, math, STEM, recent, younger, demographic, shortly, group, summer, undergrads, former, now, seniors, past, linked, communicating, prizes, capacity, finding, becoming, more, getting, 

# data[].attributes.subject
contribute, age, frequently, grow, code, optional, drawing, wanes, data, position, too, percent, tech career, range spacious, quarter, field, years, physics, young, part 14, 25, 39, capacity, fastest, easiest, long-term, changing, reflect, lots, among, often, like, still, technology, generation, engineering, computer, scientist, non-profit, telecommunications, couple, decades, fewer, biggest, doctor, math, STEM, recent, younger, demographic, shortly, group, summer, undergrads, former, now, seniors, past, linked, communicating, prizes, capacity, finding, becoming, more, getting, 

# data[].attributes.body
Reduce, increase, per cent

# data[].attributes.body
Sizes

# data[].attributes.body
Funding

# data[].attributes.body
Making decisions, stated, times, small, minutes, comply, between, number, information, different, repetition, repeating, kinetics, visual, answer, exponentially, flipped, technology, environmental.

# data[].attributes.body
Value