Diebold Descriptive Analytics.Rmd

---
title: "**Diebold Descriptive Analytics**"
date: "February 23, 2019"
output: html_document
---

##**Importing Data**
```{r}
diebold <- read.csv("December Non-bill calls.csv", stringsAsFactors = FALSE)
View(diebold)
```

##**Necessary Packages**
```{r message=FALSE, warning=FALSE}
library(qdap)
library(dplyr)
library(ggplot2)
```

##**Attribute Analysis**
**Call Text**
```{r}
call_text <- diebold$Call.Text

clean_call_text_reduced <- call_text %>%
  tolower() %>%
  removePunctuation() %>%
  removeNumbers() %>%
  stripWhitespace() %>%
  removeWords(stopwords("en"))

freq_terms_reduced <- freq_terms(clean_call_text_reduced)
plot(freq_terms_reduced)
freq_terms_reduced
```

**Billing Notes**
```{r}
billing_notes <- diebold$Billing.Notes

clean_billing_notes_reduced <- billing_notes %>%
  tolower() %>%
  removePunctuation() %>%
  removeNumbers() %>%
  stripWhitespace() %>%
  removeWords(stopwords("en"))

freq_terms_reduced <- freq_terms(clean_billing_notes_reduced)
plot(freq_terms_reduced)
freq_terms_reduced
```

**Branch Description**
```{r}
br_branch_desc <- diebold$Br.Branch.Desc

clean_br_branch_desc_reduced <- br_branch_desc %>%
  tolower() %>%
  removePunctuation() %>%
  removeNumbers() %>%
  stripWhitespace() %>%
  removeWords(stopwords("en"))

freq_terms_reduced <- freq_terms(clean_br_branch_desc_reduced)
plot(freq_terms_reduced)
freq_terms_reduced
```

**Item Description**
```{r}
item_desc <- diebold$Item.Desc

clean_item_desc_reduced <- item_desc %>%
  tolower() %>%
  removePunctuation() %>%
  removeNumbers() %>%
  stripWhitespace() %>%
  removeWords(stopwords("en"))

freq_terms_reduced <- freq_terms(clean_item_desc_reduced)
plot(freq_terms_reduced)
freq_terms_reduced
```

**SR Duration**

This was an attribute we created from the difference of SR Contact Date and Activity Completed Date to show total time that it took to complete each instance. 
```{r}
median(diebold$Difference)
mean(diebold$Difference) 
range(diebold$Difference)
Diff.Count <- diebold %>%
  group_by(Difference) %>%
  summarize(Count = n())
head(Diff.Count)
```

**Activity Type**
```{r}
diebold %>%
  group_by(Activity.Type) %>%
  summarize(Count = n()) %>%
  arrange(desc(Count))
```