Sameera's Submission

FinalRExercise_BoppanaSameera.R

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+
+
+nys_schools <- read.csv("data/nys_schools.csv", stringsAsFactors=FALSE)
+View(nys_schools)
+
+nys_acs <- read.csv("data/nys_acs.csv", stringsAsFactors=FALSE)
+View(nys_acs)
+
+
+summary(nys_acs)
+summary(nys_schools)
+
+
+nys_schools_clean <- nys_schools %>% filter(total_enroll != -99) %>% filter(per_free_lunch != -99) %>% 
+filter(mean_ela_score != -99) %>% filter(mean_math_score != -99) 
+
+
+summary(nys_schools_clean)
+
+nys_acs$poverty_classification <- as.factor(ifelse(nys_acs$median_household_income < 46347, 'High',
+                                                   ifelse(nys_acs$median_household_income < 50134, 'Medium', 'Low')))
+
+summary(nys_acs)
+view(nys_acs)
+
+mean_math <- mean(nys_schools_clean$mean_math_score)
+sd_math <- sd(nys_schools_clean$mean_math_score)
+nys_schools_clean[math_zscore] = nys_schools_clean$mean_math_score - 
+
+
+
+#1. For each county: total enrollment, percent of students qualifying for free or reduced price lunch, and percent of population in poverty.
+
+
+
+view(nys_schools_clean)
+nys_schools_clean$total_enroll_country <- 'NA'
+total_enroll_country <- nys_schools_clean %>%  group_by(county_name) %>% total_enroll
+view(total_enroll_country)