webbedfeet

from pathlib import Path
import tarfile

with tarfile.open('data.tar','w') as tar:
  for name in Path('.').glob('*/filtered_feature_bc_matrix.h5'):
    tar.add(name)
 

webbedfeet

syntax on
filetype plugin indent on
set number
set path+=**
set noswapfile
set undofile
set incsearch
set smartindent
set ic
set expandtab

webbedfeet

def df_diff(d1, d2):
    """
    df_diff Create a DataFrame containing rows of d1 not in d2

    Arguments:
        d1 -- A data frame
        d2 -- Another DataFrame which is a subset of d1

    Returns:
        A pandas DataFrame containing rows of d1 that are not in d2

webbedfeet

# For a description of this file, please see:
# https://www.innoq.com/en/blog/markdown-with-zotero-workflow
#------------------------------------------------------------

# what's the name of the generated output file(s)
OUTPUT=out

# what's the name of the markdown source file
SOURCE=principles-content.md

webbedfeet

---
creation date: <% tp.file.creation_date() %>
tags: DailyNote <% tp.file.title.split('-')[0] %>
---

modification date: <%+ tp.file.last_modified_date("dddd Do MMMM YYYY HH:mm:ss") %> // This doesn't currently work in front matter, hoping that gets fixed.

# <% tp.file.title %>

<< [[<% tp.date.now("YYYY-MM-DD", -1, tp.file.title, "YYYY-MM-DD") %>]] | [[<% tp.date.now("YYYY-MM-DD", 1, tp.file.title, "YYYY-MM-DD") %>]]>>

webbedfeet

---
title: "Example dashboard"
output: 
    flexdashboard::flex_dashboard:
        orientation: columns
        vertical_layout: scroll
    html_document: default
---

```{r setup, include=FALSE}

webbedfeet

# remotes::install_github('ramikrispin/coronavirus')
library(coronavirus)
update_datasets()
pacman::p_load(char=c('tidyverse','janitor', 'ggrepel'))

deaths <- coronavirus %>% 
  clean_names() %>% 
  filter(type=='death') %>% 
  group_by(country_region, date) %>% 
  summarise(cases = sum(cases)) %>% 

webbedfeet

# https://stackoverflow.com/questions/25191620/
#   creating-lowpass-filter-in-scipy-understanding-methods-and-units

import numpy as np
from scipy.signal import butter, lfilter, freqz
from matplotlib import pyplot as plt


def butter_lowpass(cutoff, fs, order=5):
    nyq = 0.5 * fs

webbedfeet

#' ---
#' title: An annotated R script for Homework 6 using lists and maps
#' output: html_document
#' ---
#' 
#+, include=FALSE
knitr::opts_chunk$set(error=F, warning=F, message=F)
#' First, read the data in. We've stored just the data files in the folder `data/HW6`.

library(tidyverse)

webbedfeet

#!/user/bin/bash

sqlite3 -header -csv MyDB.sqlite3 "select * from tbl;" > tbl.csv