Python Para Analise De Dados - 3a Edicao Pdf

Ana's first project involved analyzing a dataset of user engagement on a popular social media platform. The dataset included user demographics, the type of content they engaged with, and the frequency of their engagement. Ana's goal was to identify patterns in user behavior that could help the platform improve its content recommendation algorithm.

# Filter out irrelevant data data = data[data['engagement'] > 0] With her data cleaned and preprocessed, Ana moved on to exploratory data analysis (EDA) to understand the distribution of variables and relationships between them. She used histograms, scatter plots, and correlation matrices to gain insights. Python Para Analise De Dados - 3a Edicao Pdf

# Plot histograms for user demographics data.hist(bins=50, figsize=(20,15)) plt.show() Ana's first project involved analyzing a dataset of

She began by importing the necessary libraries and loading the dataset into a Pandas DataFrame. # Filter out irrelevant data data = data[data['engagement']

And so, Ana's story became a testament to the power of Python in data analysis, a tool that has democratized access to data insights and continues to shape various industries.

# Split the data into training and testing sets X = data.drop('engagement', axis=1) y = data['engagement'] X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)