maguro 1.0.1

Maguro is a lightweight manager for delimiter-separated values.

Maguro

Maguro is a lightweight manager for delimiter-separated values.

package import

from maguro import Maguro

basic usage

dataset = Maguro("dataset.csv")

custom encoding

dataset = Maguro("dataset.csv", encoding="utf-8")

custom delimiter

dataset = Maguro("dataset.tsv", delimiter="\t")

clear

Remove all items inside the list by using dataset.clear() method.

add items

Use dataset.append(value) to add new item in the list.

sorting

Use dataset.sort() to sort the list alphabetically. Optional parameter: reverse = True | False (default)

reverse

Use dataset.reverse() to reverse the list.

remove item

Use dataset.pop(value) to to remove the first occurence in the list.

to formatted string

Return a formatted string, concatenated by the specificied delimiter, by using dataset.pack() method.

raw list

Return a raw list (of list data type) by using dataset.unpack() method.

loop over items

When looping over a Maguro dataset, use .items() method to yield one item at a time. Sort list: sort True | False (default) Reverse list: reverse: True | False (default)

for item in dataset.items():
    print(item)

for item in dataset.items(sort=True):
    print(item)

for item in dataset.items(sort=True, reverse=True):
    print(item)

remove item

Remove existing (or non-existing) value. Usage: dataset.remove(value)

insert item

Insert data at a specific index Usage: dataset.insert(index, value)

load list

Loading new data into a Maguro object will replace previous contents. Usage: dataset.load(iterable)

extend list

Extending original lists follows the same list syntax. Usage: dataset.extend(iterable)

remove duplicates

Maguro leverages Python list(set()) casting to remove duplicates. Usage: dataset.remove_duplicates()

numeric methods

The items in the dataset must be an integer or a float to get a valid result. The basic usage is dataset.method() or use dataset.method(precision=2) to define the number of decimal places.

precision = -1 (default), 0 = integer, 1 - 16 float

numbers = Maguro("numbers.csv")
numbers.load([8.5,  0,  5,  14.2, 23.68,  -4,  -18,  12,  20])
print("Mean:", numbers.mean())
print("Mean (5 decimal places):", numbers.mean(precision=5))
print("Median:", numbers.median())
print("Mode:", numbers.mode())
print("Mode (whole number):", numbers.mode(precision=0))
print("Range:", numbers.dataset_range())
print("Minimum:", numbers.minimum())
print("Maximum:", numbers.maximum())