Visualize chapter count, paragraph count, word count per reading level #24
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WalkthroughThe changes involve modifications to multiple files within the project, primarily enhancing data processing and visualization capabilities. Key updates include the addition of a new column for average word length in the data preprocessing script, the introduction of exploratory data analysis (EDA) functionalities, and the inclusion of PNG files in the Git commit process. A new utility function for calculating average word length is also added, along with corresponding tests to ensure its accuracy. Additionally, a README file is created to document visualizations related to text metrics, and a new dependency for Matplotlib is introduced. Changes
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Actionable comments posted: 6
Outside diff range and nitpick comments (1)
pmml/step1_prepare/step1_4_eda.py (1)
6-7: Consider using a configuration file or command-line argument for the CSV file path.Instead of hardcoding the CSV file path, consider using a configuration file or command-line argument to make the script more flexible and reusable.
Review details
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Review profile: CHILL
Files ignored due to path filters (9)
pmml/step1_prepare/step1_2_storybooks.csvis excluded by!**/*.csvpmml/step1_prepare/step1_4_avg_word_length_hist.pngis excluded by!**/*.pngpmml/step1_prepare/step1_4_avg_word_length_scatter.pngis excluded by!**/*.pngpmml/step1_prepare/step1_4_chapter_count_hist.pngis excluded by!**/*.pngpmml/step1_prepare/step1_4_chapter_count_scatter.pngis excluded by!**/*.pngpmml/step1_prepare/step1_4_paragraph_count_hist.pngis excluded by!**/*.pngpmml/step1_prepare/step1_4_paragraph_count_scatter.pngis excluded by!**/*.pngpmml/step1_prepare/step1_4_word_count_hist.pngis excluded by!**/*.pngpmml/step1_prepare/step1_4_word_count_scatter.pngis excluded by!**/*.png
Files selected for processing (7)
- .github/workflows/pmml-nightly.yml (1 hunks)
- pmml/run_all_steps.py (1 hunks)
- pmml/step1_prepare/README.md (1 hunks)
- pmml/step1_prepare/step1_2_preprocess_data.py (2 hunks)
- pmml/step1_prepare/step1_4_eda.py (1 hunks)
- pmml/utils/chapters_utils.py (2 hunks)
- pmml/utils/test_chapters_utils.py (1 hunks)
Additional context used
Markdownlint
pmml/step1_prepare/README.md
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Ruff
pmml/run_all_steps.py
9-9:
step1_prepare.step1_4_edaimported but unusedRemove unused import:
step1_prepare.step1_4_eda(F401)
Additional comments not posted (9)
.github/workflows/pmml-nightly.yml (1)
33-33: LGTM!The addition of
git add step1_prepare/*.pngin the "Git Commit" step is a valid change that aligns with the PR objective and the AI-generated summary. Staging the PNG files from thestep1_preparedirectory ensures they are included in the nightly build commit, which is necessary for the visualization feature.pmml/step1_prepare/step1_4_eda.py (2)
10-18: LGTM!The scatter plots are generated correctly using the appropriate DataFrame columns, and the plots are saved as PNG files with meaningful file names.
20-32: LGTM!The histograms are generated correctly using the appropriate DataFrame columns and reading levels, and the plots are saved as PNG files with meaningful file names. The legend is also added correctly to distinguish between the different reading levels.
pmml/step1_prepare/step1_2_preprocess_data.py (4)
19-19: LGTM!The addition of the new column
avg_word_lengthto thestorybooks_dataframeand initializing it to 0 is appropriate. The actual values for this column will be populated later in the script.
33-35: LGTM!The average word length is correctly calculated using the
chapters_utils.get_avg_word_lengthutility function and the result is appropriately stored in theavg_word_lengthcolumn of thestorybooks_dataframeat the corresponding index.
39-39: LGTM!Including the
avg_word_lengthcolumn in the list of columns to keep when dropping unnecessary columns from thestorybooks_dataframeis necessary to ensure that it is part of the resulting dataset.
Line range hint
1-52: Excellent work!The changes made to the
step1_2_preprocess_data.pyscript are well-structured and enhance the data processing capabilities by introducing a new metric: the average word length of chapters in the storybooks. The script follows a logical flow and handles missing values, converts the reading level to a number, and correctly writes the resulting dataframe to a CSV file.The addition of the
avg_word_lengthcolumn provides valuable insights into the text structure of the storybooks and will be useful for further analysis. The usage of thechapters_utils.get_avg_word_lengthutility function is appropriate and the calculated values are correctly stored in the corresponding column and index of the dataframe.Overall, the changes are consistent with the summary of changes and improve the functionality of the script. Great job!
pmml/utils/test_chapters_utils.py (2)
84-91: LGTM!The test function
test_get_avg_word_length_when_no_paragraphsis well-implemented and covers an important edge case scenario where the JSON input contains chapters without any paragraphs. Asserting that the expected output is0ensures that theget_avg_word_lengthfunction correctly handles the absence of text.
93-100: LGTM!The test function
test_get_avg_word_length_when_single_paragraphsis well-implemented and covers a common scenario where the JSON input contains chapters with a single paragraph each. By calculating the average word length across these paragraphs and asserting the expected result, it ensures that theget_avg_word_lengthfunction correctly processes the text and returns the accurate average word length.
pmml/run_all_steps.py
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| @@ -6,6 +6,7 @@ | |||
| import step1_prepare.step1_1_download_data | |||
| import step1_prepare.step1_2_preprocess_data | |||
| import step1_prepare.step1_3_split_data | |||
| import step1_prepare.step1_4_eda | |||
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Tip
Codebase Verification
Unused Import Detected: Review the necessity of step1_prepare.step1_4_eda
The module step1_prepare.step1_4_eda is imported in pmml/run_all_steps.py but is not used anywhere else in the codebase. This suggests that the import might be unnecessary. Please review whether this module should be integrated into the codebase or if the import can be safely removed to avoid maintenance overhead.
- File:
pmml/run_all_steps.py - Line: 9
Analysis chain
Verify the usage of the imported module.
The import statement for step1_prepare.step1_4_eda is syntactically correct. Based on the provided context, this import is intentional and aims to introduce exploratory data analysis (EDA) functionalities, which aligns with the objectives of enhancing the data processing and visualization capabilities.
To verify the correctness and effectiveness of the imported module, I recommend reviewing the implementation of step1_prepare.step1_4_eda and ensuring that it is being used appropriately within the codebase to achieve the desired EDA functionalities. Consider running the following script to check for the usage of the imported module:
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify the usage of the imported module `step1_prepare.step1_4_eda`.
# Test: Search for the usage of the module. Expect: At least one occurrence.
rg --type python -w $'step1_4_eda'
Length of output: 64
Script:
#!/bin/bash
# Description: Verify the usage of the imported module `step1_prepare.step1_4_eda`.
# Test: Search for the usage of the module. Expect: At least one occurrence.
rg --glob '*.py' -w 'step1_4_eda'
Length of output: 88
Tools
Ruff
9-9:
step1_prepare.step1_4_edaimported but unusedRemove unused import:
step1_prepare.step1_4_eda(F401)
Which issue does this PR address?
#21
Summary by CodeRabbit
New Features
Documentation
Bug Fixes
Tests