lsloan

-- Fill in the name of your DB in @dbname then run the following as the admin user, should be all updated to utf8mb4!

-- mysql --silent < generateAlter.sql > alterTables.sql
-- mysql < alterTables.sql

SET @dbname = "myla_dev";

use information_schema;
-- Update DB to utf8mb4
SELECT "SET FOREIGN_KEY_CHECKS=0;";

lsloan

1. Substitute the NaN's in a dataframe with values from another dataframe

If you have two DataFrames of the same shape, then:

df[df.isnull()] = d2



2.Replace values in a dataframe with values from another dataframe by conditions

lsloan

def recursiveFormat(args, **kwargs):
    """
    Recursively apply `string.format()` to all strings in a data structure.

    This is intended to be used on a data structure that may contain
    format strings just before it is passed to `json.dump()` or `dumps()`.
    
    Ideally, I'd like to build this into a subclass of `json.JsonEncoder`,
    but it's tricky to separate out string handling in that class.  I'll
    continue to think about it.

lsloan

# -*- coding: utf-8 -*-
import functools

from django.contrib.admin import ModelAdmin
from django.contrib.admin.options import InlineModelAdmin
from django.contrib.admin.utils import flatten_fieldsets
from django.core.exceptions import ObjectDoesNotExist
from django.db.models import OneToOneField, ForeignKey
from django.forms import ModelForm
from django.forms.models import BaseModelFormSet, modelformset_factory

lsloan

A collapsible section containing markdown

Click to expand!

Heading

1. A numbered
2. list
   • With some
   • Sub bullets

lsloan

jupyter:
  image: jupyter/datascience-notebook
  environment:
    - PASSWORD=${PASSWORD}


nginx:  
  image: nginx
  links: 
    - jupyter

lsloan

## Initial setup you should only have to do this once
# Checkout docker stacks project
git clone https://github.com/jupyter/docker-stacks

cd docker-stacks/base-notebook

# Clone the telemetry in this directory, this is currently a private repo. 
git clone https://github.com/educational-technology-collective/hwf-jupyterlab-telemetry	

# git needs to be added to base image

lsloan

Examples of processing QTI data with Python.

I attempted to use pyslet, which was designed for this purpose, but I found it awkward to use and its documentation unclear. Instead, I tried to use beautifulsoup4, but I learned that library doesn't support XPath to query for specific elements of the data. I turned to using the simple XML processing library lxml. It has similarities to other XML parsing libraries I've used before, but it has many unique features of its own.

Note that of the examples below, each does something a little differently. They don't all have the same output.
That's because they were mostly tests to see whether we preferred working with one library over another. Some

lsloan

Cisco AnyConnect: auto login in silent mode

This gist is for Linux. For windows is the same thing.

Connect

create a file .login_info as below:

connect your.server.url    
usernanme 

lsloan

# Add field
echo '{"hello": "world"}' | jq --arg foo bar '. + {foo: $foo}'
# {
#   "hello": "world",
#   "foo": "bar"
# }

# Override field value
echo '{"hello": "world"}' | jq --arg foo bar '. + {hello: $foo}'
{