How to evaluate readability using Python?

Introduction

How can you evaluate “Readability“?

Textstat is an easy-to-use library to calculate statistics from the text. It helps determine readability, complexity, and grade level.

For example, The Flesch Reading Ease Score is the score of readability which indicates how difficult a passage in English is to understand. And the score is described below.

If you want to know that score, you can calculate it by using textstat;

textstat.flesch_reading_ease(text)

If the returned value is 45.8, the text is difficult. And if 77.03, Fairly Easy.

In addition to this, you can calculate other readability scores;

• The Flesch Reading Ease formula
• The Flesch-Kincaid Grade Level
• The Fog Scale (Gunning FOG Formula)
• The SMOG Index
• Automated Readability Index
• The Coleman-Liau Index
• Linear Write Formula
• Dale-Chall Readability Score And
• Readability Consensus-based upon all the above tests

You can also count the number of

• Syllable
• Lexicon
• Sentence

by using textstat.

Load data

import numpy as np
import pandas as pd

train = pd.read_csv('/kaggle/input/commonlitreadabilityprize/train.csv')
test = pd.read_csv('/kaggle/input/commonlitreadabilityprize/test.csv')
sub = pd.read_csv('/kaggle/input/commonlitreadabilityprize/sample_submission.csv')
train

2834 rows × 6 columns

# The row with the min target value
train_min = train.loc[train['target'].idxmin()]
excerpt_min = train_min['excerpt']
print(train_min)
print()
print(excerpt_min)

# The row with the max target value
train_max = train.loc[train['target'].idxmax()]
excerpt_max = train_max['excerpt']
print(train_max)
print()
print(excerpt_max)

Textstat

Textstat is an easy to use library to calculate statistics from text.
It helps determine readability, complexity, and grade level.

We will use;

• textstat.flesch_reading_ease(test_data)
• textstat.smog_index(test_data)
• textstat.flesch_kincaid_grade(test_data)
• textstat.coleman_liau_index(test_data)
• textstat.automated_readability_index(test_data)
• textstat.dale_chall_readability_score(test_data)
• textstat.difficult_words(test_data)
• textstat.linsear_write_formula(test_data)
• textstat.gunning_fog(test_data)
• textstat.text_standard(test_data)

The following functions are specifically designed for spanish language.
They can be used on non-spanish texts, even though that use case is not recommended.

• textstat.fernandez_huerta(test_data)
• textstat.szigriszt_pazos(test_data)
• textstat.gutierrez_polini(test_data)
• textstat.crawford(test_data)

!pip install textstat

import textstat

List of Functions

syllable_count

Returns the number of syllables present in the given text.
Uses the Python module Pyphen for syllable calculation.

print(textstat.syllable_count(excerpt_min))
print(textstat.syllable_count(excerpt_max))

285
201

lexicon_count

Calculates the number of words present in the text. Optional remove punct specifies whether we need to take punctuation symbols into account while counting lexicons. The default value is True, which removes the punctuation before counting lexicon items.

print(textstat.lexicon_count(excerpt_min, removepunct=True))
print(textstat.lexicon_count(excerpt_max, removepunct=True))

177
145

Sentence Count

Returns the number of sentences present in the given text.

print(textstat.sentence_count(excerpt_min))
print(textstat.sentence_count(excerpt_max))

7
13

Flesch Reading Ease

Returns the Flesch Reading Ease Score.
The following table can be helpful to assess the ease of readability of a document.
The table is an example of values. While the maximum score is 121.22, there is no limit on how low the score can be. A negative score is valid.

Formula

print(textstat.flesch_reading_ease(excerpt_min))
print(textstat.flesch_reading_ease(excerpt_max))

45.8
77.03

The Flesch-Kincaid Grade Level

Returns the Flesch-Kincaid Grade of the given text.
This is a grading formula in that a score of 9.3 means that a ninth-grader would be able to read the document.

Formula;

print(textstat.flesch_kincaid_grade(excerpt_min))
print(textstat.flesch_kincaid_grade(excerpt_max))

13.2
5.3

Gunning fog index

Returns the FOG index of the given text. This is a grading formula in that a score of 9.3 means that a ninth-grader would be able to read the document.

Formula;

# gunning_fog by textstat
print(textstat.gunning_fog(excerpt_min))
print(textstat.gunning_fog(excerpt_max))

14.64
6.69

SMOG

Returns the SMOG index of the given text.
This is a grading formula in that a score of 9.3 means that a ninth-grader would be able to read the document.
Texts of fewer than 30 sentences are statistically invalid because the SMOG formula was normed on 30-sentence samples. textstat requires at least 3 sentences for a result.

• Count a number of sentences (at least 30)
• In those sentences, count the polysyllables (words of 3 or more syllables).

# smog_index by textstat
print(textstat.smog_index(excerpt_min))
print(textstat.smog_index(excerpt_max))

14.6
8.4

Automated readability index

Returns the ARI (Automated Readability Index) which outputs a number that approximates the grade level needed to comprehend the text.

For example, if the ARI is 6.5, then the grade level to comprehend the text is 6th to 7th grade.

Formula;

print(textstat.automated_readability_index(excerpt_min))
print(textstat.automated_readability_index(excerpt_max))

15.0
8.8

The Coleman-Liau Index

Returns the grade level of the text using the Coleman-Liau Formula. This is a grading formula in that a score of 9.3 means that a ninth-grader would be able to read the document.

CLI=0.0588L−0.296S−15.8

• LL : the average number of letters per 100 words
• SS : the average number of sentences per 100 words.

print(textstat.coleman_liau_index(excerpt_min))
print(textstat.coleman_liau_index(excerpt_max))

11.44
10.88

Linsear Write Formula

Returns the grade level using the Linsear Write Formula. This is a grading formula in that a score of 9.3 means that a ninth-grader would be able to read the document.

Formula;
The standard Linsear Write metric LwLw runs on a 100-word sample:

1. For each “easy word”, defined as words with 2 syllables or less, add 1 point.
2. For each “hard word”, defined as words with 3 syllables or more, add 3 points.
3. Divide the points by the number of sentences in the 100-word sample.
4. Adjust the provisional result r:

• If r>20,Lw=r/2r>20,Lw=r/2
• If r≤20,Lw=r/2−1r≤20,Lw=r/2−1

The result is a “grade level” measure, reflecting the estimated years of education needed to read the text fluently.

print(textstat.linsear_write_formula(excerpt_min))
print(textstat.linsear_write_formula(excerpt_max))

16.75
5.222222222222222

Dale–Chall readability formula

Different from other tests, it uses a lookup table of the most commonly used 3000 English words. Thus it returns the grade level using the New Dale-Chall Formula.

print(textstat.dale_chall_readability_score(excerpt_min))
print(textstat.dale_chall_readability_score(excerpt_max))

8.19
6.37

# difficult_words
print(textstat.difficult_words(excerpt_min))
print(textstat.difficult_words(excerpt_max))

37
20

Readability Consensus-based upon all the above tests

Based upon all the above tests, returns the estimated school grade level required to understand the text. Optionally float_output allows the score to be returned as a float. Defaults to False.

print(textstat.text_standard(excerpt_min))
print(textstat.text_standard(excerpt_max))

14th and 15th grade
6th and 7th grade

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