School District analysis using python pandas library to inform school district board in order to help funding decisions.

Datasets: school dataset containing information for district and charter schools. The school dataset also contains school size and budget.

The second dataset is a student dataset containing: gender, grade, school name, reading and math score, type of school, size, and budget.

Step 1:

Set dependencies (Pandas) and read in the two csv files.

Step 2:

Analyze school district data and create summary information for the 7 schools within the district. The summary table contained total students, total budget, avg. math score, avg. reading score, passing math and reading, and percent overall passing.

To do so utilized conditionals, value counts, and mean.

Step 3:

Created a school level summary of all schools, district and charter, showing; type of school, total students, total school budget, per student budget, avg. math and reading scores, percent passing math, percent passing reading, and overall passing.

Step 4:

Created a summary table for top 5 and bottom five schools containing; showing; type of school, total students, total school budget, per student budget, avg. math and reading scores, percent passing math, percent passing reading, and overall passing.

Step 5:

Created a dashboard that lists the average math score for sutdents in: 9th, 10th, 11th, 12th grades at each school.

Created a dashboard that lists the average reading score for students in: 9th, 10th, 11th, 12th grades at each school.

-Created a dashboard that scores school spending in connection to the following categories:

-Average math score, -Average reading score, -Percentage passing math, -Percentage passing reading, -Percentage overall passing