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Welcome to this directory of learning notebooks focused on data analysis with Python. These notebooks are sourced from an online course, carefully curated to provide practical insights and techniques for aspiring data analysts.

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Data Analysis Learning Notebooks

Welcome to this directory of learning notebooks focused on data analysis with Python. These notebooks are sourced from an online course, carefully curated to provide practical insights and techniques for aspiring data analysts.

Contents:

  1. Exploratory Data Analysis (EDA): Dive into exploratory techniques, data visualization, and statistical summaries. Understand how to clean and preprocess data effectively.
  2. Pandas and Data Wrangling: Learn about the powerful pandas library for data manipulation. Explore DataFrames, indexing, merging, and aggregation.
  3. Statistical Analysis: Discover essential statistical concepts and methods. Apply hypothesis testing, correlation analysis, and regression.
  4. Visualization and Reporting: Master data visualization using libraries like Matplotlib and Seaborn.
  5. Create informative charts, graphs, and dashboards. Feel free to explore these notebooks and enhance your data analysis skills. If you have any questions or need further guidance, don’t hesitate to reach out.

Happy learning! 🚀📊

Buku Catatan Pembelajaran Analisis Data

Selamat datang di direktori buku catatan pembelajaran yang berfokus pada analisis data dengan Python. Buku catatan ini bersumber dari kursus online, yang disusun dengan cermat untuk memberikan wawasan dan teknik praktis bagi calon analis data.

Isi:

  1. Analisis Data Eksplorasi (EDA): Selami teknik eksplorasi, visualisasi data, dan ringkasan statistik. Pahami cara membersihkan dan memproses data terlebih dahulu secara efektif.
  2. Panda dan Perselisihan Data: Pelajari tentang perpustakaan pandas yang ampuh untuk manipulasi data. Jelajahi DataFrames, pengindeksan, penggabungan, dan agregasi.
  3. Analisis Statistik: Temukan konsep dan metode statistik penting. Terapkan pengujian hipotesis, analisis korelasi, dan regresi.
  4. Visualisasi dan Pelaporan: Visualisasi data master menggunakan perpustakaan seperti Matplotlib dan Seaborn.
  5. Buat bagan, grafik, dan dasbor yang informatif. Jangan ragu untuk menjelajahi buku catatan ini dan meningkatkan keterampilan analisis data Anda. Jika Anda memiliki pertanyaan atau memerlukan panduan lebih lanjut, jangan ragu untuk menghubungi kami.

Selamat belajar! 🚀📊

Warning

This module is in mixed language: Indonesian and English

Modul ini dalam bahasa campuran: Bahasa Indonesia dan Inggris

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Welcome to this directory of learning notebooks focused on data analysis with Python. These notebooks are sourced from an online course, carefully curated to provide practical insights and techniques for aspiring data analysts.

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