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BroaderImpact / ds-alg.ipynb
Created September 25, 2022 22:06
Python Data Structures and Algorithms
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BroaderImpact / BRR_final.ipynb
Last active February 18, 2023 17:01
BRR Data Analysis
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BroaderImpact / sample.ipynb
Last active February 16, 2023 23:02
NDWA sample
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BroaderImpact / README.md
Last active February 18, 2023 16:49
ML Model Selection

GitHub contributors GitHub issues GitHub Packagist Stars

ml-model-selection

Easy python script for determining which machine learning model to use.

Installation

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BroaderImpact / EDA.md
Last active February 18, 2023 17:35
Exploratory Data Analysis

GitHub contributors GitHub issues GitHub Packagist Stars GitHub code size in bytes

Exploratory Data Analysis

Automated python script for running preliminary exploratory data analysis on csv input.

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BroaderImpact / iic.md
Last active February 18, 2023 17:52
Assembling Geospatial Data for Interactive Map of Organizations

Assembling Geospatial Data for Interactive Map of Organizations

Coordinating the work of a coalition is difficult on a local level. The problem is further compounded for statewide and national coordination. The need for clear, concise visualization of organizations committed to the cause of IIC was presented by a member organization.

import folium

# Create a map object
map = folium.Map(location=[37.0902, -95.7129], zoom_start=4)
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BroaderImpact / lipid.ipynb
Last active February 19, 2023 19:04
Lipidomic Analysis Workflow Using LipidR
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BroaderImpact / pipeline.py
Created February 18, 2023 21:33
GCP Data Pipeline
# Import the required libraries
import subprocess
import os
# Set the GCS bucket and BigQuery dataset and table names
BUCKET_NAME = "my-bucket"
DATASET_NAME = "my-dataset"
TABLE_NAME = "my-table"
# Set the names for local files
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BroaderImpact / Rnaseq.ipynb
Created February 19, 2023 17:43
RNASeq Pipeline in R
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BroaderImpact / PKPD.R
Last active March 19, 2023 21:38
Pipeline for Pharmacokinetics/Pharmacodynamics in R
# Pharmacokinetics
# load necessary packages
library(dplyr)
library(nlme)
library(plotly)
# read in data
data <- read.csv("drug_trial_data.csv")