Exploratory Data Analysis in Python: Analyzing New Datasets — LearnFlat

Exploratory Data Analysis in Python: Analyzing New Datasets

Learn how to confidently open, clean, and extract initial insights from any unfamiliar dataset using modern Python libraries and structured analytical workflows.

3.8 (18) ⏱ 2 godz 30 min 📚 25 lekcji

O tym kursie

Facing a brand-new dataset can feel overwhelming when you do not know where to start looking for patterns. This text-based course teaches you how to systematically approach, audit, and understand any dataset from scratch using Python. You will transition from staring at raw rows of data to confidently extracting meaningful stories, identifying anomalies, and preparing data for deeper modeling. You will master the foundational habits that professional data analysts use to inspect data quality and uncover hidden relationships. What you'll learn: - Understand the foundational principles of exploratory data analysis and how to structure your initial inquiry. - Clean and preprocess raw data by handling missing values, duplicates, and incorrect data types. - Apply modern Pandas techniques and explore high-performance alternatives like Polars for efficient data manipulation. - Analyze numerical and categorical distributions using descriptive statistics and correlation matrices. - Write robust, readable data analysis code using modern Python practices, including basic type hints. - Identify outliers and anomalies that could skew your analytical results or machine learning models. You will begin by learning core terminology and the philosophy of data exploration before moving into step-by-step written explanations and code-based exercises. The material guides you logically from initial file loading to advanced multi-variable relationship analysis. This course is designed for aspiring data analysts, researchers, and beginners who have a basic grasp of Python syntax and want to develop practical data-wrangling skills. No advanced mathematics or prior data science experience is required. Start reading today to build a structured, professional workflow for analyzing any dataset you encounter.

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  • 📱 Telefon lub komputer
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  • 💸 Zwrot w 14 dni
    Bez pytań
  • Krótko i konkretnie
    2 godz 30 min praktycznej treści

Recenzje (18)

Peter Amponsah GH Zweryfikowany kursant
★ 5 · 03.07.2026

Fantastic course. The examples used were spot on and really helped solidify the concepts. My understanding has improved dramatically.

Oka Pratama ID Zweryfikowany kursant
★ 4 · 03.07.2026

Informative and well-organized. Could benefit from more varied examples in later modules.

Maria Vasileiou GR Zweryfikowany kursant
★ 4 · 29.06.2026

Pretty good introduction. The examples were helpful, but I wish there was a bit more practice material. Solid value for the cost.

Anna Kowalska PL
★ 4 · 29.06.2026

A useful introduction. The explanations were generally clear, but a few concepts required extra digging.

Eduardo Barbosa BR Zweryfikowany kursant
★ 4 · 29.06.2026

A good introduction. The structure was mostly clear, but I wish there were a few more real-world examples. Still, learned a lot.

Andrew Owusu GH Zweryfikowany kursant
★ 4 · 29.06.2026

It's a good course if you have some prior knowledge. For absolute beginners, some concepts might be a bit challenging. The structure is logical, though.

Sophia Heyns ZA
★ 5 · 28.06.2026

A truly excellent learning experience. The flow was logical and the examples were super helpful.

Makeda Solomon ET
★ 3 · 27.06.2026

Found it useful. The flow was logical, and the illustrative examples helped solidify the ideas. Could have used a bit more depth.

Juana Morales PA
★ 3 · 18.06.2026

It's a decent introduction. Could benefit from more diverse examples and a slightly better flow between modules.

Arturo Rivas PE Zweryfikowany kursant
★ 5 · 11.06.2026

Couldn't have asked for a better learning experience. The structure flowed perfectly, and the examples were incredibly relevant. Highly recommend!

Анна Козлова RU
★ 3 · 08.06.2026

It's a solid course. The structure is logical and most of the examples were helpful. Could use a few more real-world scenarios though.

Olamide Adeyemi NG Zweryfikowany kursant
★ 4 · 08.06.2026

Co za wspaniałe doświadczenie edukacyjne! Przepływ informacji był doskonały, a ćwiczenia praktyczne były kluczowe.Bardzo zadowolony z tego.

راضية بن عبد الرحمان TN Zweryfikowany kursant
★ 3 · 05.06.2026

Found it useful for a refresher. Not sure it would be the best starting point for a complete beginner, tbh.

Benjamin Taylor NZ Zweryfikowany kursant
★ 3 · 04.06.2026

Szkolenie: Struktura była logiczna, ale chciałbym, aby było więcej praktycznych ćwiczeń poza podstawowymi przykładami.

Alice Robert BE
★ 3 · 03.06.2026

Hmm, I'm not sure this is for absolute beginners. It assumes a bit of prior knowledge that wasn't explicitly taught. Some examples were confusing.

Alejandro Ramírez EC Zweryfikowany kursant
★ 3 · 31.05.2026

Hmm, I'm not sure this is ideal for beginners. Some concepts were glossed over, and the examples weren't always clear.

Francisca Pereira BR
★ 4 · 28.05.2026

This course exceeded my expectations! The examples were spot-on and really helped solidify the learning. Definitely worth the time.

César Romero PA Zweryfikowany kursant
★ 5 · 27.05.2026

Fantastic learning experience. The pace was perfect and the examples really clarified things. Definitely worth the time.

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Najczęstsze pytania

Czego potrzebuję, by wziąć udział w tym kursie? +

Wystarczy telefon lub komputer z internetem. Bez instalacji i specjalnego sprzętu.

Jak zapłacić? +

Kartą przez Stripe. Nie przechowujemy danych karty — robi to bezpiecznie Stripe.

Czy mogę otrzymać zwrot? +

Tak — pełen zwrot w 14 dni, bez pytań.

Jak długo będę mieć dostęp? +

Na zawsze. Po zakupie kurs jest twój — wracaj, kiedy chcesz.

Czy dostanę certyfikat? +

Tak. Po ukończeniu otrzymasz certyfikat, który możesz dodać do profilu LinkedIn.

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