upbeta01

[[ 9 15]
 [-2  2]]

upbeta01

upstream containers {
    server 0.0.0.0:9000;
    server 0.0.0.0:9001;
    server 0.0.0.0:9002;
    server 0.0.0.0:9003;
}

server {
    listen 80;
    server_name hostname;

upbeta01

#!/bin/bash

docker image prune -a -f
eval $(aws ecr get-login --no-include-email --region us-west-2)

j=0
for i in  {9000..9003}
  do
    PORT=$i
    COUNT=$((j++))

upbeta01

FROM node:16

WORKDIR /usr/src/app
COPY . .

RUN npm install
RUN npm run build

EXPOSE YOUR_PORT
CMD [ "npm", "run", "serve"]

upbeta01

// File: main.rs
fn main() {
    // This code prints the lyrics of the song: "The Twelve Days of Christmas"
    // Sing with me with these lines of code!

    let mut count = 0;
    let mut item_checkout: Vec<&str> = Vec::new();
    let days: [&str; 12] = [
        "1st", "2nd", "3rd", "4th", "5th", "6th", "7th", "8th", "9th", "10th", "11th", "12th",
    ];

upbeta01

Keybase proof

I hereby claim:

• I am upbeta01 on github.
• I am upbeta01 (https://keybase.io/upbeta01) on keybase.
• I have a public key ASA3d-gtyDk-k3omqag_Zo7Ob5qXY9FSvDKejmR967K-BAo

To claim this, I am signing this object:

upbeta01

import pandas as pd

# Load the data from the CSV file
df = pd.read_csv("weather_data.csv")

# Group by city and calculate the max and mean temperatures for both temperature_f and temperature_c
agg_data_f = df.groupby("city")["temperature_f"].agg(["max", "min", "mean"])
agg_data_c = df.groupby("city")["temperature_c"].agg(["max", "min", "mean"])

# Get fluctuation per city