arrpy 1.0.0

arrpy is a 2D array manipulation module

Arrpy

A lightweight module allowing simple manipulation of 2D arrays using base python list objects. Designed for use in pandas-incompatible situations, such as when working in Jython. Allows import and export of spreadsheets, finding the mean across rows or columns, and row extraction.

download

run 'pip install arrpy'

Import and export

open_df(file, delim_type = "csv", subarray = "col", e = 'utf-8-sig') Open file and return a corresponding list of lists. file is a string denoting the path of the 2D data of interest. delim type is a string denoting the column separators used in file. Currently accepts "csv" and "tab". subarray is a string denoting whether the respective subarrays in the list created will correspond to a row or a columns of file. e is a string denoting the encoding of the file.

write_csv(arr, path, subarray = "col") Write arr to file. arr is a list of lists. file is a string denoting the path to write to. subarray is a string denoting whether the respective subarrays in arr will correspond to a row or column of file.

List manipulation

append_row(arr, row, base_check = True, deep = True) Output a new list object with row appended to arr. arr is a list of lists. row is a list to append to arr. base_check is a boolean to determine whether to run a set of basic compatibilty checks on arr (type, length, dimension count, and raggedness) deep is a boolean to determine whether to append row to a deep (True) or shallow copy of arr (False).

del_row(arr, row, base_check = True) Output a new list object with row deleted from arr. arr is a list of lists. row is an object that is coercible to 0 <= int <= len(arr[0]). base_check is a boolean to determine whether to run a set of basic compatibilty checks on arr (type, length, dimension count, and raggedness)

List processing

avg_col(arr, base_check = True, dim_check = False) Outputs the arithmetic mean of the columns (subarrays) of arr as a list. arr is a list of lists. base_check is a boolean to determine whether to run a set of basic compatibilty checks on arr (type, length, dimension count, and raggedness) dim_check is a boolean to determine whether to check if arr has a consistent number of dimensions. This can be slow for larger arr.

avg_row(arr, base_check = True, dim_check = False) Outputs the arithmetic mean of the rows (a given index of each subarray) of arr as a list. arr is a list of lists. base_check is a boolean to determine whether to run a set of basic compatibilty checks on arr (type, length, dimension count, and raggedness) dim_check is a boolean to determine whether to check if arr has a consistent number of dimensions. This can be slow for larger arr.

row_extract(arr, row, base_check = True) Outputs the selected row (given index of each subarray of arr) as a list. arr is a list of lists. row is an object that is coercible to 0 <= int <= len(arr[0]). base_check is a boolean to determine whether to run a set of basic compatibilty checks on arr (type, length, dimension count, and raggedness) dim_check is a boolean to determine whether to check if arr has a consistent number of dimensions. This can be slow for larger arr.