metacalc.Rmd

---
title: "Calculator Log Meta Analysis"
author: Tan
---


```{r warning=FALSE}

library(DBI)
library(odbc)
library(tidyverse)
library(hrbrthemes)

aws_db <- dbConnect(odbc(),'dynastyprocess_db')

calculator_logs <- dbGetQuery(aws_db,'SELECT * FROM dp_calculatorlogs')

df_calc <- calculator_logs

dbDisconnect(aws_db)
```

```{r}

calc_types <- calculator_logs %>% 
  count(input_calctype)

calc_types
```

```{r}

draft_types <- calculator_logs %>% 
  count(input_drafttype)

draft_types
```
```{r}
qb_type <- calculator_logs %>% 
  count(input_qb)
qb_type
```



```{r}
calculator_logs %>% 
  # count(input_valuefactor) %>%
  mutate(input_teams = parse_number(input_teams),
         trade_diffs = abs(teamA_total-teamB_total),
         trade_pct = pmap_dbl(list(trade_diffs,teamA_total,teamB_total),~..1/min(..2,..3))) %>%
  filter(trade_diffs <= 10000,is.finite(trade_pct)) %>% 
  # filter(trade_pct <=1) %>% 
  ggplot() +
  geom_step(aes(trade_pct),stat = 'ecdf',color = 'green',size = 1) +
  coord_cartesian(xlim = c(0,1))+
  # xlim(c(0,1))+
  # geom_line(aes(x = ecdf(df$trade_diffs))) +
  # geom_bar(aes(x = ecdf(trade_diffs))) +
  theme_modern_rc()

```

```{r}

```