Part 1
Today the puzzle got a bit trickier than Day 1.
The submarine seems to already have a planned course (your puzzle input). You should probably figure out where it's going. For example: forward 5 down 5 forward 8 up 3 down 8 forward 2 Your horizontal position and depth both start at 0. The steps above would then modify them as follows: forward 5 adds 5 to your horizontal position, a total of 5. down 5 adds 5 to your depth, resulting in a value of 5. forward 8 adds 8 to your horizontal position, a total of 13. up 3 decreases your depth by 3, resulting in a value of 2. down 8 adds 8 to your depth, resulting in a value of 10. forward 2 adds 2 to your horizontal position, a total of 15. After following these instructions, you would have a horizontal position of 15 and a depth of 10. (Multiplying these together produces 150.) Calculate the horizontal position and depth you would have after following the planned course. What do you get if you multiply your final horizontal position by your final depth?
So Pandas here we go again:
df = pd.read_csv("./aoc_day_02_data.txt", delimiter=" ",header=None) df.columns = ["command", "value"]
Alright, reading in the data and naming the columns are the same steps as yesterday. Now we have to columns.
0 | 1 | |
---|---|---|
0 | forward | 5 |
1 | down | 5 |
2 | forward | 8 |
3 | up | 3 |
4 | down | 8 |
5 | forward | 5 |
horizontal = df[df['command']=="forward"]["value"].sum()
The horizontal value can be calculated with the sum function when we filter the data frame to rows where the command is “forward”
depth = df[df['command']=="down"]["value"].sum() - df[df['command']=="up"]["value"].sum()
The depth can calculated by summing up the down and up commands separately and subtract the sums from each other.
Now we have to multiply the depth and the position to get the solution
position = depth * horizontal
Part 2
down X increases your aim by X units. up X decreases your aim by X units. forward X does two things: It increases your horizontal position by X units. It increases your depth by your aim multiplied by X. Now, the above example does something different: forward 5 adds 5 to your horizontal position, a total of 5. Because your aim is 0, your depth does not change. down 5 adds 5 to your aim, resulting in a value of 5. forward 8 adds 8 to your horizontal position, a total of 13. Because your aim is 5, your depth increases by 8*5=40. up 3 decreases your aim by 3, resulting in a value of 2. down 8 adds 8 to your aim, resulting in a value of 10. forward 2 adds 2 to your horizontal position, a total of 15. Because your aim is 10, your depth increases by 2*10=20 to a total of 60. After following these new instructions, you would have a horizontal position of 15 and a depth of 60. (Multiplying these produces 900.) Using this new interpretation of the commands, calculate the horizontal position and depth you would have after following the planned course. What do you get if you multiply your final horizontal position by your final depth?
To get an overview I simplified the table
a d f 5 0 0 d 5 5 f 8 5 40 u 3 2 d 8 10 f 2 10 20
Here I had a hard time to do it with pandas so vanilla python to the rescue:
if __name__ == '__main__': with open("./aoc_day_02_data.txt") as file: lines = file.readlines() lines = [line.rstrip() for line in lines] horizontal = 0 current_aim = 0 depth = 0 for line in lines: print(line) command, value = line.split(" ") value = int(value) if command == "forward": horizontal += value depth += value * current_aim if command == "down": current_aim += value if command == "up": current_aim += value * -1 print(f"horizontal: {horizontal}") print(f"depth: {depth}") print(horizontal * depth)
Update
I’ve figured out how to do it with Pandas as well
import pandas as pd df = pd.read_csv("./aoc_day_02_test_data.txt", delimiter=" ",header=None) df.columns = ["command", "value"] horizontal = df[df['command']=="forward"]["value"].sum() df.loc[df['command']=="up", "value"] = df[df['command']=="up"].mul(-1) df["aim"] = 0 df.loc[df['command']!="forward", "aim"] = df[df['command']!="forward"]["value"] df["current_aim"] = df["aim"].cumsum() df.loc[df['command']=="forward", "depth"] = df[df['command']=="forward"]["value"] * df[df['command']=="forward"]["current_aim"] depth = df["depth"].sum()