Plot a calendar in python using matplotlib. The days are drawn on a 7*52 heatmap grid, with the months clearly delineated.
Slightly cleaned up from https://gist.github.com/rsnape/98bbf68e333b0948192e found in this Stack Overflow answer
Plot a calendar in python using matplotlib. The days are drawn on a 7*52 heatmap grid, with the months clearly delineated.
Slightly cleaned up from https://gist.github.com/rsnape/98bbf68e333b0948192e found in this Stack Overflow answer
Expenses in red below, income in green above, over time on the x axis, value on y axis.
You can see this chart at: http://bl.ocks.org/galvanic/284b254c6fe3a501d8bcc46c95e6f601
| #!/usr/bin/env python | |
| # coding: utf-8 | |
| import numpy as np | |
| import pandas as pd | |
| import re | |
| #import os ## TODO use this to traverse folders | |
| from email.parser import Parser | |
| from sklearn.feature_extraction.text import CountVectorizer |
| cat *.ipynb | jq '.cells' | jq -c '.[] | select(.cell_type | contains("markdown"))' | jq -c '. | select(.source[] | contains("#")) | .source[]' | grep "#" | sed 's/"//g' | sed 's/\\n//g' | sed 's/#/\t/g' | sed 's/\(.*\)\t/\1-/' |
A simple upset chart implementation, a chart type useful for visualising set intersections, applied to flatmate-purchase assignment data from my onlineshop project.
See it live on bl.ocks
metrics AUC FNR FPR error_test error_train
classifier attack % poisoned GD method
adaline empty 0.0 mini-batch 0.94 0.00 0.12 0.03 0.01
stochastic 0.58 0.65 0.20 0.54 0.51
batch 0.93 0.00 0.14 0.03 0.01
0.5 mini-batch 0.92 0.01 0.15 0.04 0.01
stochastic 0.45 0.57 0.53 0.56 0.29
batch 0.90 0.02 0.19 0.06 0.00
| default_parameters: | |
| experiment: adaptive combination | |
| dataset_filename: enron-kayla | |
| label_type: | |
| ham_label: -1 | |
| spam_label: 1 |
| default_parameters: | |
| experiment: adaptive combination | |
| dataset_filename: enron-kayla | |
| label_type: | |
| ham_label: -1 | |
| spam_label: 1 |
| default_parameters: | |
| experiment: adaptive combination | |
| dataset_filename: enron-kayla | |
| label_type: | |
| ham_label: -1 | |
| spam_label: 1 |
| default_parameters: | |
| experiment: adaptive combination | |
| dataset_filename: enron-kayla | |
| label_type: | |
| ham_label: -1 | |
| spam_label: 1 |