Koala

What is the library?

Python's pandas implemented for fast, type safe programming in Rust.

Available Functions & Attributes

• CSV

  .read_csv(path: &str) -> CSV

  returns CSV struct reading file from given path rust let mut content = String::new(); let csv : CSV = dataframe::df::read_csv("test.csv", &mut content); // CSV { headers, values, matrix }

  .get_df() -> DataFrame

  returns DataFrame from a CSV struct rust let mut df = csv.get_df(); // DataFrame { columns, dataset, values }

• DataFrame

  .columns -> Vec<&str>

  returns array of strings, containing column names rust df.columns; // ["name","age"]

  ### .dataset -> Vec> returns dataset matrix rust df.dataset; // [["bob","30"] ["richard", "25"]]

  ### .values -> Vec)> returns vector of pairs, containing column name, and all column values rust df.values; // [("name", ["bob", "richard"]), ("age", ["30", "25])]

  ### .max(column: &str) -> f64 returns max from all values inside a column rust df.max("age"); // 30 as f64

  ### .max(column: &str) -> f64 return min from all values inside a column rust df.min("age"); // 25 as f64

  ### .mean(column: &str) -> f64 return mean from all values inside a column rust df.mean("age"); // 27.5 as f64

  .sum(column: &str) -> f64

  returns sum of all non N/A values from column rust df.sum("age"); // 55 as f64

  ### [&str] -> Vec<&str> string index for DataFrame, returns all values from a given column rust df["age"]; // ["30", "25"]

  ### [usize] -> Vec<&str> usize index for DataFrame, returns given row with all columns rust df[0]; // ["bob", "30"]

  ### .iloc(Vec, Range>) -> Vec> returns sliced dataset matrix from given range rust df.iloc([0..2, 0..1].to_vec()); // [["richard"], ["bob"]]

  ### .isnacol(column: &str) -> bool returns if given column on DataFrame has a missing value rust df.is_na_col("age"); // false

  ### .is_na() -> bool returns matrix containing missing value bool for each value rust df.is_na(); // [[false, false], [false, false]]

  ### .push(value: Vec<&str>) returns matrix containing missing value bool for each value rust df.push(["ann", "20"]); df.dataset; // [["richard", "30"], ["bob", "25"], ["ann", "20"]]

  ### .pop(value: Vec<&str>) -> Vec<&str> returns matrix containing missing value bool for each value rust df.pop(); // ["ann", "20"] df.pop(); // ["bob", "25"] df.dataset; // [["richard", "30"]]

  ### .n_uniques(column: &str) -> usize returns matrix containing missing value bool for each value rust df.n_uniques("age"); // 2 as usize

  ### .uniques(column: &str) -> Vec<&str> returns matrix containing missing value bool for each value rust df.uniques("age"); // ["30", "25"]

  ### .apply(column: &str, function: for<'r> fn(&'r str) -> &'a str) applies closure function to each value on given column rust fn in_my_twenties<'r>(age: &str) -> &'r str { "20" } df.apply("age", in_my_twenties); df.dataset; // [["richard", "20"], ["bob", "20"]]

  .fillna(column: &str, value: &str)

  assigns given value to each N/A value on column rust df.fillna("age", df.mean("age")); // [["richard", "26"], ["bob", "26"]] given bob had no prior age