Lecture 1: Introduction to Research — [📝Lecture Notebooks] [
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[
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import subprocess | |
import requests | |
import psutil | |
def get_notebooks(host, port, token = None): | |
sessions_url = f'http://{host}:{port}/api/sessions/?token={token}' if token else f'http://{host}:{port}/api/sessions' | |
response = requests.get(sessions_url).json() | |
notebooks = [{'kernel_id': notebook['kernel']['id'], | |
'path': notebook['notebook']['path']} for notebook in response] |
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function concat_with_header() { | |
# Quoted suffix to pattern match for concatenation (e.g. '*.csv') | |
local suffix="${1}" | |
# Name of the output file | |
local output="${2:-combined.out}" | |
# Number of lines to use for the header | |
local header_length="${3:-1}" | |
# Grab the header from the first file | |
local header=`echo -e "$(ls -b *$suffix | head -n$header_length)"` | |
head -1 $header_file > $output; tail -n +"`expr $header_length + 1`" -q *$suffix >> $output |
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package greenlight.etc | |
import java.security.SecureRandom | |
import kotlin.math.abs | |
val BASE58_ALPHABET = "23456789ABCDEFGHJKLMNPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz" | |
fun randomBase58(length: Int): String { |
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[Unit] | |
Description=AutoSSH tunnel service | |
After=network-online.target sshd.service | |
[Service] | |
Environment="AUTOSSH_GATETIME=0" | |
Environment="AUTOSSH_PORT=0" | |
ExecStart=/usr/bin/autossh -o "ServerAliveInterval 10" -o "ServerAliveCountMax 3" -N -R 2222:localhost:22 -R 8888:localhost:8888 user@middlman.dev | |
[Install] |
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import numpy as np | |
def shrink_df(df, categorize=False, verbose=False): | |
"""Reduces the memory use of a data frame by using more compact types. | |
Args: | |
df (pandas.DataFrame): The dataframe | |
categorize (bool): Whether strings should be converted to categorical values. | |
Note this may cause memory use to increase slightly. | |
verbose (bool): Whether to print memory savings to stdout. |
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# icd10_map_charlson from https://github.com/jackwasey/icd/blob/master/data/icd10_map_charlson.RData | |
df = data.frame("comorbidity" = character(0), "icd10" = character(0), "score" = numeric(0), stringsAsFactors = FALSE) | |
scores = data.frame( | |
MI = 1, | |
CHF = 1, | |
PVD = 1, | |
Stroke = 1, | |
Dementia = 1, |
I hereby claim:
- I am fny on github.
- I am fny (https://keybase.io/fny) on keybase.
- I have a public key whose fingerprint is 477B 6E2F 415F 02BC AA6C 44E0 1E9C CF9B 131E 417C
To claim this, I am signing this object:
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