For my project, I performed exploratory data analysis (EDA) on the Titanic dataset. This dataset contains information about the passengers who were on board the Titanic, and it is a classic dataset in the field of data science.
During my EDA process, I used various techniques to analyze the data and draw conclusions. For example, I used descriptive statistics to understand the distribution of variables such as age and fare. I also created visualizations such as histograms and box plots to further explore these variables and identify any outliers or unusual patterns.
Additionally, I used correlation analysis to investigate relationships between variables, such as the correlation between age and survival. I also used feature engineering to create new variables based on existing ones, such as creating a variable to represent family size.
After performing these various techniques, I was able to draw several conclusions about the data. For example, I found that there was a higher survival rate among women and children, as well as among passengers in higher passenger classes. I also found that there was a negative correlation between age and survival, indicating that younger passengers were more likely to survive.
Overall, my project involved performing thorough EDA on the Titanic dataset and using various techniques to draw insightful conclusions about the data.