fbrundu

# line number after ==
# change \\t with the delimiter you want to use instead of tab for splitting to words
words_count=$(awk 'NR==5{print}' data.csv | tr \\t \\n | wc -l)
unique_words_count=$(awk 'NR==5{print}' data.csv | tr \\t \\n | uniq | wc -l)

if [[ "$words_count" -ne "$unique_words_counts" ]]; then
    echo "Not unique"
else
    echo "Unique"

fbrundu

import pandas as pd
import sys
import glob
import os

# input / output directory
input_dir = sys.argv[1]
# input file extension
input_ext = sys.argv[2]
# cardinality of index columns (rownames)

fbrundu

import pandas as pd
import numpy as np
import sys
import random as rnd

csv = sys.argv[1]
out = sys.argv[2]

df = pd.read_table(csv, sep='\t', index_col=0)

fbrundu

import pandas as pd
import sys
import re

tcga_tsv = sys.argv[1]

tcga = pd.read_table(tcga_tsv, sep='\t', index_col=0)

oldcolumns = tcga.columns.tolist()
newcolumns = ['-'.join(re.findall(r'TCGA[^_]*', oc)[0].split('-')[:4])

fbrundu

<style>

html {
  font-size: 62.5% !important; }
body {
  font-size: 1.5em !important; /* currently ems cause chrome bug misinterpreting rems on body element */
  line-height: 1.6 !important;
  font-weight: 400 !important;
  font-family: "HelveticaNeue", "Helvetica Neue", Helvetica, Arial, sans-serif !important;
  color: #222 !important; }

fbrundu

.CodeMirror, div.prompt.input_prompt, div.prompt.output_prompt, pre {
    font-family: "Inconsolata for Powerline";
    font-size: 100%;
}

fbrundu

import fastcluster as fc
import pandas as pd
import scipy.cluster.hierarchy as sch

# define total number of cluster to obtain
k = 5

# define matrix path
mat_path = 'matrix.txt'

fbrundu

import pandas as pd

# load data
mat = pd.read_table('class_matrix.txt', index_col=0)

# initialize consensus array
consensus_a = pd.Series(index=mat.index)

# define columns subset on which compute consensus
# in this case all columns are used

fbrundu

import numpy as np
import pandas as pd

# load data
mat = pd.read_table('matrix.txt', index_col=0)

# get classes
classes = np.unique(mat.values)
classes = classes[~np.isnan(classes)]

fbrundu

" no vi-compatible
set nocompatible

let g:python_host_prog=$HOME.'/.pyenv/versions/neovim2/bin/python'
let g:python3_host_prog=$HOME.'/.pyenv/versions/neovim3/bin/python'

" Setting up Vundle - the vim plugin bundler
let iCanHazVundle=1
let vundle_readme=expand('~/.vim/bundle/vundle/README.md')
if !filereadable(vundle_readme)