# Mini-Project B3: ## On methodology <!-- Put the link to this slide here so people can follow --> - Sally, Magnus, Emilio and Jonathan --- # Why the how? *Very good question* --- ## Step 1 - The dataset  20.814 rows later  --- ## Step 2 - Moving to pandas ``` python= import pandas as pd co2_df = pd.read_csv("./co2_emission.csv") print(co2_df) ```  --- ## Step 3 - Dirty data? ```python= print(co2_df.isnull().sum()) ```  ---- #### Step 3.5 :bath: - Cleaning data ```python= co2_df_noCode = co2_df.drop(labels="Code", axis=1) print(co2_df_noCode) ```  --- ## Step 4 - Visualizing the data ```python= def make_graph(country): title = country + " Co2 Emissions" co2_df_country = co2_df[co2_df["Entity"] == country] co2_df_country.plot( x="Year", y="Annual CO₂ emissions (tonnes )", title=title ) make_graph("Denmark") ``` ---- ## Step 4.5 - The graph for Denmark  --- ## Step 5 - Going worldwide ```python= def graph_world(): hasOccured = []; for country in co2_df["Entity"]: if(country in hasOccured): continue else: hasOccured.append(country) for country in hasOccured: make_graph(country) graph_world() ``` ----  #### Now what? --- ## Step 6 - Understanding the visualization ```python= make_graph("World") ```  le10? ---- - The data ```python= co2_df_world = co2_df[co2_df["Entity"] == "World"] print(co2_df_world) ```  3.615326e+10? ----  ##### The highest annual worldwide emission of CO~2~ > People alive today :shocked_face_with_exploding_head: --- ## Step 6.5 - What about Denmark?  ---- ```python= co2_df_dk = co2_df[co2_df["Entity"] == "Denmark"] co2_df_dk_highest = co2_df_dk.sort_values( by=['Annual CO₂ emissions (tonnes )'], ascending=False ) print(co2_df_dk_highest) ```   ##### How many cars would it take to produce that much CO~2~? ---- > "A typical passenger vehicle emits about ==4.6 metric tons== of carbon dioxide per year" ([epa.gov](https://https://www.epa.gov/greenvehicles/greenhouse-gas-emissions-typical-passenger-vehicle), 2018) ---- $\frac{74877499.12}{4.6} = 16.277.717,2$  ##### It would take ==16 million cars== to produce the amount of CO~2~ emitted in Denmark in 1996 ---- #### Which correlates to about 3 times the amount of people in Denmark in 1996  :thinking_face: