diff --git a/.DS_Store b/.DS_Store index b1f811b..21c159c 100644 Binary files a/.DS_Store and b/.DS_Store differ diff --git a/PDF to CSV Challenge_ School Schedule Transformation.html b/PDF to CSV Challenge_ School Schedule Transformation.html new file mode 100644 index 0000000..dda94d5 --- /dev/null +++ b/PDF to CSV Challenge_ School Schedule Transformation.html @@ -0,0 +1,936 @@ + + + + + + PDF to CSV Challenge: School Schedule Transformation + + + + +
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2 Lessons | 80 minutes
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1
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Data Transformation Challenge

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Convert a school schedule from PDF format to structured CSV data

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+ Two 40-minute lessons +
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Real-world skill: PDF data extraction is a common task in data analysis, administrative work, and automation projects.

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+ + + Schedule.pdf + Input file + + + + + Template.csv + Target format + +
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+ Download both files before starting the challenge +

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Lesson Plan
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2
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Two-Lesson Structure

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Lesson 1: Analysis & Extraction

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Focus: Understanding the data and planning the extraction

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  • 10 min - Introduction to PDF data extraction
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  • 15 min - Analyze Schedule.pdf structure
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  • 10 min - Choose tools and methods
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  • 5 min - Begin data extraction
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Lesson 2: Transformation & Validation

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Focus: Cleaning data and creating the final CSV

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  • 10 min - Review and clean extracted data
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  • 15 min - Transform to CSV format
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  • 10 min - Validate against template
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  • 5 min - Discussion and reflection
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Pro tip: Take notes during Lesson 1 about the PDF structure. This will save time in Lesson 2.

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Challenge Overview
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3
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The Challenge

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Your Mission:

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Transform unstructured schedule data from a PDF into a structured CSV file.

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1
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Extract

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Get data out of the PDF file using Python libraries or tools

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2
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Clean

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Organize the messy, unstructured text into logical groups

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3
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Transform

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Convert the data to match the CSV template format

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4
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Validate

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Check that your CSV matches the expected structure

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Input File
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4
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Input: Schedule.pdf

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This PDF contains unstructured school schedule data with:

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  • Days of week in Russian (Пн, Вт, Ср, Чт, Пт)
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  • Time slots (1-13 with specific times)
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  • Class information (subject, class, room)
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  • Teacher name at the bottom
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PDF Content Preview:

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+01.09.2025 +aSc Расписание +6A/6B ICT B24 Ict1 +2А/2В/2С Maths B24 E5 +7C/7D ICT B24 Ict1 +... +Пн Вт Ср Чт Пт +1 9:00 - 9:40 +2 10:00 - 10:40 +... +Учитель Bob Santos +
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Challenge: The data is unstructured - you'll need to find patterns to extract it correctly.

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Output File
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5
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Output: Template.csv

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Your goal is to create a CSV file matching this structure:

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  • First row: Column headers (Day, time slots)
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  • Each row: A day of the week (Monday-Friday)
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  • Cells: Class information or empty if no class
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  • Multi-line cells for detailed class info
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CSV Structure Preview:

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+Day,1 (9:00-9:40),2 (10:00-10:40),3 (11:00-11:40)... +Monday,,"Subject: Maths Class: 2А/2В/2С E5 +Room: B24",,,"Subject: ICT Class: 6A/6B Room: B24"... +Tuesday,"Subject: Технотрек Class: 7A/7B/7C/7D/7E Room: B24, B02"... +
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Note: Notice how class information is formatted as "Subject: ... Class: ... Room: ..."

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Tools
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6
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Recommended Tools

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Choose from these options for the data extraction:

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PyPDF2

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Basic PDF text extraction

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pdfplumber

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Advanced table extraction

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tabula-py

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Extract tables from PDF

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pandas

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Data cleaning & CSV export

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Tabula (GUI)

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Visual table extraction tool

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Manual

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Copy-paste & clean in spreadsheet

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Suggestion: Start with pdfplumber for Python or Tabula GUI if you're new to PDF extraction.

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Tips
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7
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Key Considerations

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Important Details to Notice:

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1
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Russian to English

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Convert Пн, Вт, Ср, Чт, Пт to Monday, Tuesday, Wednesday, Thursday, Friday

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2
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Time Slots

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Match class information to the correct time slots (1-13 with specific times)

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3
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Formatting

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Follow the exact format: "Subject: ... Class: ... Room: ..." in CSV cells

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4
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Empty Cells

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Leave cells empty for time slots with no classes

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Common Challenges:

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  • Handling multi-room assignments (e.g., "B24,B02")
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  • Dealing with split classes (e.g., "6A/6B")
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  • Identifying which classes belong to which time slots
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  • Managing multi-line cells in the CSV
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Reflection
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8
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Discussion Questions

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After completing the challenge, consider these questions:

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  • What was the most challenging part of extracting data from the PDF?
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  • How did you handle the Russian day abbreviations?
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  • What pattern recognition strategies worked best?
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  • How would you validate that all data was extracted correctly?
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  • If the PDF format changed next semester, how could you make your solution more flexible?
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  • What real-world applications can you think of for PDF data extraction skills?
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    Learning outcome: This challenge develops problem-solving, pattern recognition, and data transformation skills applicable to many real-world scenarios.

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    + + + Instructions + Detailed guide + +
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    + + + + \ No newline at end of file diff --git a/Schedule.pdf b/Schedule.pdf new file mode 100644 index 0000000..4305ca7 Binary files /dev/null and b/Schedule.pdf differ diff --git a/repo_chat_bots/.DS_Store b/repo_chat_bots/.DS_Store index a0da7cf..25d1364 100644 Binary files a/repo_chat_bots/.DS_Store and b/repo_chat_bots/.DS_Store differ diff --git a/repo_chat_bots/yandex-chat-app/.DS_Store b/repo_chat_bots/yandex-chat-app/.DS_Store new file mode 100644 index 0000000..00fb8d1 Binary files /dev/null and b/repo_chat_bots/yandex-chat-app/.DS_Store differ diff --git a/training_data/Schedule.png b/training_data/Schedule.png new file mode 100644 index 0000000..6a91b09 Binary files /dev/null and b/training_data/Schedule.png differ