Загрузка страницы

EDA using Pandas Profiling | YData Profiling Part 2

🚀 Welcome back to Part 2 of our ydata_profiling video! In this video, we dive into a new case study using the Google Play Store dataset from Kaggle.

Dataset Link - https://www.kaggle.com/datasets/gauthamp10/google-playstore-apps

📊 We'll demonstrate how ydata_profiling can be used to generate a profile report for this dataset, showcasing its powerful features and capabilities.

🔍 One of the highlights of this video is the use of word clouds generated by ydata_profiling for object-type features with too many categories. These word clouds provide a visual representation of the most common words in these features, offering valuable insights into the dataset at a glance.

📈 Additionally, we'll explore a new feature called "compare," which allows us to compare the profile reports of the train and test sets of a dataset. This feature makes it easy to observe the differences in the properties of the two sets, helping us gain a deeper understanding of the dataset's characteristics.

🔥 Whether you're a data enthusiast looking to explore new datasets or a seasoned data scientist seeking innovative tools for data analysis, this video is packed with valuable information and insights.

📝 Subscribe to our channel for more tutorials on cutting-edge data analysis tools and techniques.

Видео EDA using Pandas Profiling | YData Profiling Part 2 канала Six Sigma Pro SMART
Показать
Комментарии отсутствуют
Введите заголовок:

Введите адрес ссылки:

Введите адрес видео с YouTube:

Зарегистрируйтесь или войдите с
Информация о видео
15 марта 2024 г. 17:30:39
00:10:23
Другие видео канала
The A to Z of Logistic Regression | All that you need to know | Supervised Learning | Data ScienceThe A to Z of Logistic Regression | All that you need to know | Supervised Learning | Data ScienceThe A to Z of Feature Encoding | Label Encoding | One Hot Encoding | Data Preprocessing in PythonThe A to Z of Feature Encoding | Label Encoding | One Hot Encoding | Data Preprocessing in PythonEnsemble Machine Learning Technique: VotingEnsemble Machine Learning Technique: VotingHands-on Hyperparameter Tuning | Grid SearchHands-on Hyperparameter Tuning | Grid SearchImportance of Weight Initialization in Neural Networks | Deep Learning basicsImportance of Weight Initialization in Neural Networks | Deep Learning basicsComplete guide to hands-on A/B Testing | A/B testing in Python | All that you need to knowComplete guide to hands-on A/B Testing | A/B testing in Python | All that you need to knowANOVA: Behind the scenes | Uncover the logic | Hypothesis Testing | Data ScienceANOVA: Behind the scenes | Uncover the logic | Hypothesis Testing | Data ScienceThe A to Z of Support Vector Machines | All you need to know | Supervised Learning | Data ScienceThe A to Z of Support Vector Machines | All you need to know | Supervised Learning | Data ScienceThe journey of a neuron | Geometric intuitionThe journey of a neuron | Geometric intuitionText Preprocessing | Case Conversion | Unwanted Patterns | Stopwords | Stemming | LemmatizationText Preprocessing | Case Conversion | Unwanted Patterns | Stopwords | Stemming | LemmatizationGetting started with Neural NetworksGetting started with Neural NetworksHands-on Text Preprocessing in Python Part 2 | Natural Language Processing  basicsHands-on Text Preprocessing in Python Part 2 | Natural Language Processing basicsPython: Regular Expressions for beginnersPython: Regular Expressions for beginnersVisual Explanation | Solved Example | Paired t test | Dependent Samples t test | Hypothesis TestingVisual Explanation | Solved Example | Paired t test | Dependent Samples t test | Hypothesis TestingThe journey of a neuron | The PerceptronThe journey of a neuron | The PerceptronGetting the best results from your ML models | Youden's IndexGetting the best results from your ML models | Youden's IndexHands-on Feature Selection in Python | Choose just the right features for your model | Data ScienceHands-on Feature Selection in Python | Choose just the right features for your model | Data ScienceWhat is Point-Biserial correlation? | Theory + Hands-on | All that you need to knowWhat is Point-Biserial correlation? | Theory + Hands-on | All that you need to knowConfusion Matrix | Classification Accuracy Precision Recall | Supervised Machine LearningConfusion Matrix | Classification Accuracy Precision Recall | Supervised Machine LearningStep-by-step guide to TF IDF | Natural Language Processing basicsStep-by-step guide to TF IDF | Natural Language Processing basicsThe A to Z of Linear Regression | All that you need to know | Supervised Learning | Data ScienceThe A to Z of Linear Regression | All that you need to know | Supervised Learning | Data Science
Яндекс.Метрика