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# Project: Exploring NYC Public School Test Result Scores

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Photo by Jannis Lucas on Unsplash.

Every year, American high school students take SATs, which are standardized tests intended to measure literacy, numeracy, and writing skills. There are three sections - reading, math, and writing, each with a maximum score of 800 points. These tests are extremely important for students and colleges, as they play a pivotal role in the admissions process.

Analyzing the performance of schools is important for a variety of stakeholders, including policy and education professionals, researchers, government, and even parents considering which school their children should attend.

You have been provided with a dataset called `schools.csv`, which is previewed below.

You have been tasked with answering three key questions about New York City (NYC) public school SAT performance.

```.mfe-app-workspace-11z5vno{font-family:JetBrainsMonoNL,Menlo,Monaco,'Courier New',monospace;font-size:13px;line-height:20px;}```# Re-run this cell
import pandas as pd

# Preview the data

# Start coding here...
# Add as many cells as you like...``````
``````# New df where schools acheived more than 80% of average maths score.
maths_80 = schools[schools['average_math'] >= 800 * 0.8]
best_math_schools = maths_80[['school_name', 'average_math']].sort_values('average_math', ascending = False)
print(best_math_schools)``````
``````# Identify top 10 schools
schools['total_SAT'] = schools['average_math'] + schools['average_reading'] + schools['average_writing']

# Top 10 schools
print(top_10_schools)``````
``````# Task 3
borough = schools.groupby('borough')['total_SAT'].agg(['count','mean', 'std']).round(2)
print(borough)

largest_std_dev = borough[borough['std'] == borough['std'].max()]

# My code
#largest_std_dev.rename(columns={'count':'num_schools','mean':'average_SAT','std':'std_SAT'})