Sea-Level-Predictor

certification python project from freecodecamp

1. using Python to predict the sea level change through year 2050.

   Prediction graphic

   

2. import libraries

   import library

        import pandas as pd
        import matplotlib.pyplot as plt
        from scipy.stats import linregress
        

3. matplotlib to create scatter plot for year and sea level from data available

   scatter plot

   def draw_plot():
          # Read data from file
          df = pd.read_csv("epa-sea-level.csv")
   
          # Create scatter plot
          plt.figure(figsize=(12,6))
          plt.scatter(data=df, 
                      x="Year", 
                      y="CSIRO Adjusted Sea Level")
        

4. scipy.stats (linregress) to make a prediction (red line) of sea level to year 2050 based on available data

   linregress

            m = linregress(x=df["Year"], 
            y=df["CSIRO Adjusted Sea Level"])
            trend = [m.slope * i + m.intercept for i in df["Year"]]
            df["trend"] = trend
            years_extended = [i for i in range(2014, 2051)]
            trend_2050 = [m.slope * i + m.intercept for i in years_extended]
            df_2050 = pd.DataFrame({"Year":years_extended, "trend":trend_2050})
            df_gabung = pd.concat([df, df_2050], ignore_index=True)
        

   scatter plot

            lt.figure(figsize=(12,6))
            plt.scatter(data=df, 
                        x="Year", 
                        y="CSIRO Adjusted Sea Level")
            plt.plot(df_gabung["Year"], df_gabung["trend"], color="red")
        

5. scipy.stats (linregress) to make a prediction (black line) of sea level to year 2050 based on selected available data (year 2000 up)

   linregress

            df_2000 = df[(df["Year"] >= 2000)]
            m_2000 = linregress(df_2000["Year"], df_2000["CSIRO Adjusted Sea Level"])
            df_2000_2050 = df_gabung[df_gabung["Year"] >= 2000].copy(deep=True)
            trend_2000_2050 = [m_2000.slope * i + m_2000.intercept for i in df_2000_2050["Year"]]
            df_2000_2050["trend_2000"] = trend_2000_2050            
        

   scatter plot

            plt.plot(df_2000_2050["Year"], df_2000_2050["trend_2000"], color="black")
        

6. add labels and title

   labels & title

            plt.xlabel("Year")
            plt.ylabel("Sea Level (inches)")
            plt.title("Rise in Sea Level")            
            plt.savefig('sea_level_plot.png')
            return plt.gca()
        

7. call via main.py