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The purpose of our analysis is to find the overall passing percentages of the students and see if there is any correlation with the budget per student using numpy-python

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School_District_Analysis

The purpose of our analysis is to find the overall passing percentages of the students and see if there is any correlation with the budget per student. What we have found is that some of the test scores from the 9th grade at Thomas High School are missing. Since these values are missing we want to take all of the scores from the high school so that it doesn't affect our overall numbers.

#How is the district summary affected?

After taking a look at both district summaries from pycityschools and pycityschools_challenge there is not a change.

#How is the school summary affected?

The over all passing for Thomas High School was 90.94% in pycityschools, with the 9th graders taken out the overall passing shrinks by 0.3 %.

#How does replacing the ninth graders’ math and reading scores affect Thomas High School’s performance relative to the other schools?

Overall it does not affect either the reading scores or math scores. We are doing an investigation because we believe they are not including most of the 9th graders scores because they might bring the school even further down in test scores.

#How does replacing the ninth-grade scores affect the following: #Math and reading scores by grade

The only difference now between the scores is that under 9th graders who attended Thomas High School it shows an NaN.

#Scores by school spending

The numbers stay nearly identical since the 9th graders are nullified from the statistics.

#Scores by school size

Overall passing percentage does not change.

#Scores by school type

Scores by school type are not altered at all.

#Conclusion

After we have replaced the scores of the 9th grade students we learn that not much has changed. We have nullified the values that we felt would alter size,district, spending and overall passing percentage of the students.

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The purpose of our analysis is to find the overall passing percentages of the students and see if there is any correlation with the budget per student using numpy-python

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