Python Para Analise De Dados | - 3a Edicao Pdf

# Handle missing values and convert data types data.fillna(data.mean(), inplace=True) data['age'] = pd.to_numeric(data['age'], errors='coerce')

# Plot histograms for user demographics data.hist(bins=50, figsize=(20,15)) plt.show() Python Para Analise De Dados - 3a Edicao Pdf

from sklearn.model_selection import train_test_split from sklearn.ensemble import RandomForestRegressor from sklearn.metrics import mean_squared_error # Handle missing values and convert data types data

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. inplace=True) data['age'] = pd.to_numeric(data['age']