reading_files.qmd

---
title: "Reading plays - dvw files"
---

## DVW files

The data project scouting software, [data volley 4](https://www.dataproject.com/Products/EN/en/Volleyball/DataVolley4) produces .dvw files. These files are similar to a text file. If your interested in some example files, you can find them [here](https://mevza.volleynet.at/Download/59).

## Python - Reading plays from one dvw file

The provided example file is used. You would typically fill in the `None` with the actual path of your dvw files.

```{python}
#| tbl-pyex: Example python reading data
from datavolley import read_dv
import pandas as pd
from IPython.display import Markdown
pd.set_option('display.max_colwidth', 1000)
dv_instance = read_dv.DataVolley(None) # Replace `None` with path of your dvw file 
df = dv_instance.get_plays()
df = df[df['skill'].notna()]
df = df.head(5)
Markdown(df.to_markdown(index = False, tablefmt="github", maxcolwidths=[None]))
```

## Python - Reading plays from multiple files

```{python}
import os

# Assign path
dvw_path_folder = os.path.expanduser("~\\desktop\\dvws")
file_extension = ".dvw"

# Get a list of all files with the specified extension in the directory
file_list = [f for f in os.listdir(dvw_path_folder) if f.endswith(file_extension)]

# Initialize an empty DataFrame to store combined data
combined_df = pd.DataFrame()

def process_file(path):
    dv_instance = read_dv.DataVolley(os.path.join(dvw_path_folder, path))
    df = dv_instance.get_plays()
    return df

# Loop through each file path
for file_name in file_list:
    combined_df = pd.concat([combined_df, process_file(file_name)], ignore_index=True)

match_count = combined_df[['match_id']].drop_duplicates()
Markdown(match_count.to_markdown(index = False))
```

------------------------------------------------------------------------

## R - Reading plays from one dvw file

The provided example file is used. You would typically fill in the `None` with the actual path of your dvw files.

```{r}
#| warning: FALSE
library(datavolley)
library(tidyverse)
x <- dv_read("datavolley//example_data.dvw") # Example data from python
px <- x$plays
px <- px %>% filter(!is.na(skill))
px <- head(px, 5)
knitr::kable(px)
```

## R - Reading plays from multiple files

```{r}
#| warning: FALSE
dvw_path_folder <- path.expand("~/dvws")
d <- dir(dvw_path_folder, pattern = "dvw$", full.names = TRUE)
lx <- lapply(d, dv_read, insert_technical_timeouts = FALSE)
px <- bind_rows(lapply(lx, plays))
match_count <- px %>% distinct(match_id)
knitr::kable(match_count)
```