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library(tidyr)
library(dplyr)
library(UpSetR)

# read in the data
ppa <- read.csv("ppa-digitizedworks-20190419T18_24_42.csv")

# subset to only needed rows and split Collection into multiple rows
new_df <- ppa %>% select("Title", "Source.ID", "Collection") %>% separate_rows("Collection", sep=";")
# give a truth column value to map on spread

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# use env to set django settings module
# env DJANGO_SETTINGS_MODULE=mep.settings python mep_cardholders.py

import csv
import codecs


import django
from django.db import models

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with open('/tmp/sylviabeach-card-images.txt') as found_images:
    urls = found_images.read().split('\n')
    identifiers = {}
    for u in urls:
        identifier = '/'.join(u.split('/')[-3:])
        identifiers[identifier] = ''


with open('/tmp/pudl0123-825298-noboxes-sorted.txt') as image_list:

meg-codes

#!/bin/bash

apt update
apt install -y make build-essential libssl-dev zlib1g-dev libbz2-dev \
  libreadline-dev libsqlite3-dev wget curl llvm libncurses5-dev libncursesw5-dev \
  xz-utils tk-dev libffi-dev liblzma-dev python-openssl git

curl https://pyenv.run | bash

# Load pyenv automatically by adding