uweziegenhagen.de

\documentclass[21pt]{scrartcl}
\usepackage[left=2cm,right=2cm, top=2cm,bottom=2cm,a3paper]{geometry}
 
\usepackage{forloop}
\setlength{\parindent}{0pt}
\usepackage{tikz}
 
\newcounter{ct} 
\usepackage{pgfpages}
 
\def\pgfpageoptionheight{\the\paperwidth} % landscaped by default
\def\pgfpageoptionwidth{\the\paperheight}
\def\pgfpageoptionborder{0pt}
\def\pgfpageoptionfirstshipout{1}
 
\pgfpagesphysicalpageoptions{%
    logical pages=8,%
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}
 
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\begin{document}%
 
\forloop{ct}{1}{\value{ct} < 9}{%
\begin{tikzpicture}
\foreach \i in {0,...,-17}{%
\draw[very thick] (0,\i*2) -- ++(0,1.5) -- ++(1.5,0) -- ++(0,-1.5)--cycle; 
\draw[very thick] (2.5,\i*2) -- (22,\i*2);
\draw[very thick] (23,\i*2) -- ++(0,1.5) -- ++(1.5,0) -- ++(0,-1.5)--cycle; 
}
\end{tikzpicture}
\clearpage
}
 
\end{document}

import sys
import collections
import pandas as pd
from tabulate import tabulate
 
 
file1 = pd.read_csv('file1.csv', sep=';', encoding='UTF-8')
file2 = pd.read_csv('file2.csv', sep=';', encoding='UTF-8')
 
columnnames1 = list(file1)
columnnames2 = list(file2)
 
if collections.Counter(columnnames1) == collections.Counter(columnnames2):
    print ("Number of columns and Names match, Comparison possible...\n\n")
else:
    print ("Number of columns and Names are not matching!!! Please check the input!")
    sys.exit('Error!')
 
# add suffixes to distinguish between actual and expected in the merger
file1 = file1.add_suffix('_e') # expected
file2 = file2.add_suffix('_t') # t
 
 
# merge them using the given key, use outer join
comparison = pd.merge(file1,file2, how='outer',
                      left_on=['Key_e'],
                      right_on=['Key_t'])
 
# create the columnwise comparison
for col in columnnames1:
    comparison[(col + '_c')] = comparison[(col + '_t')] == comparison[(col + '_e')]
 
# reorder the columns
comparison=comparison.reindex(sorted(comparison.columns),axis=1)
 
print(tabulate(comparison, tablefmt="pipe", headers="keys"))
 
 
# save the result as Excel file
comparison.to_excel('result.xlsx')
 
# names of the comparison column
check_colnames= [s + '_c' for s in columnnames1]
 
# initialize an empty dataframe for the log
logdf=pd.DataFrame(index=[True,False])
 
for column in check_colnames:
    t=comparison[column].value_counts() # returns a series
    tt=pd.DataFrame(t) # makes a DF out of the series
    logdf = logdf.join(tt,how='outer') # join the two dfs
 
# transpose for better readability
logdf = logdf.transpose()
 
# Ensure fixed sequence of the columns
logdf=logdf.reindex(sorted(logdf.columns),axis=1)
 
# write to disk
logdf.to_excel('logfile.xlsx')
 
# for better viewing on the screen
logdf.fillna('-',inplace=True)
pd.options.display.float_format = '{:,.0f}'.format
 
print(tabulate(logdf, tablefmt="pipe", headers="keys"))

gci "K:\inputpath" | Select @{N="Path Length";E={$_.FullName.Length}}, @{N="URL Length";E={$_.FullName.replace(' ','+++').Length}}, 
Fullname | Export-Csv -NoTypeInformation -Delimiter ";" -Path "t:\ABC\filelaengen.csv"

%!TEX TS-program = Arara
% arara: pdflatex: {shell: yes}
\documentclass[12pt,ngerman]{scrartcl}
\areaset{8cm}{16cm}
\usepackage[utf8]{inputenc}
\usepackage[T1]{fontenc}
\usepackage{babel}
\pagestyle{empty}
\usepackage[pattern=dot,% 
colorset=std,
geometry={left=2.25cm,right=1.25cm,top=1cm,bottom=1.25cm},%
textarea,%
patternsize={5mm},%
dotsize={1pt}
]{gridpapers}
 
\begin{document}
~
 
\end{document}

\documentclass{article}
\usepackage[T1]{fontenc}
\usepackage{graphicx}
\usepackage[landscape,paperheight=57mm,paperwidth=32mm,left=0mm,top=0mm,right=0mm,bottom=0mm]{geometry}
%\usepackage[sfdefault]{plex-sans}
\usepackage{palatino}
 
\begin{filecontents}[overwrite]{Dymo5732.tdf}
\unitlength=1mm
\hoffset=-25.4mm
\voffset=-29mm
\ticketNumbers{1}{1}
\ticketSize{57}{32} % Breite und Hoehe der Labels in mm
\ticketDistance{0}{0} % Abstand der Labels
\end{filecontents}
 
\usepackage[Dymo5732]{ticket}
 
\renewcommand{\ticketdefault}{}%
\makeatletter
\@boxedfalse % Rahmen um Ticket
\@emptycrossmarkfalse % Falzmarken
\@cutmarkfalse % Schnittmarken
\makeatother
 
\newcommand{\myticket}[2]{
\ticket{%
\put(10,10){\scalebox{#1}{\bfseries #2}}
}}
 
\newcommand{\myticketml}[4]{
\ticket{%
\put(5,20){\scalebox{#1}{\bfseries #2}}
\put(5,15){\scalebox{#1}{\bfseries #3}}
\put(5,10){\scalebox{#1}{\bfseries #4}}
}}
 
 
\begin{document}
\myticketml{1.25}{Dr. Max  Mustermann}{Musterweg 123}{54321~Musterstadt}
\myticket{2}{Steuern}
\end{document}

import pandas
import pandas_datareader.data as web
 
YAHOO_TODAY="http://download.finance.yahoo.com/d/quotes.csv?s=%s&f=sd1ohgl1vl1"
 
history = web.DataReader('AAPL', "yahoo", start="2021-1-1")
history.to_latex('aapl.tex')

\documentclass[12pt,ngerman]{scrartcl}
\usepackage[a4paper, top=1cm,bottom=1cm,left=1cm, right=1cm]{geometry}
\usepackage[T1]{fontenc}
\usepackage{booktabs}
 
\makeatletter
\newcommand{\testfileexists}[1]{%
  \IfFileExists{#1}%
    {\def\inputtestedfile{\@@input #1 }}
    {\let\inputtestedfile\@empty}%
}
\makeatother
 
\begin{document}
 
\write18{python runpy.py}
 
  \testfileexists{aapl}
      \inputtestedfile
 
 
\end{document}

#!/usr/bin/env python
# coding: utf-8
 
import seaborn as sns
import pandas as pd
import requests
from bs4 import BeautifulSoup
from io import StringIO
import matplotlib.pylab as plt
 
headers = {
    'Access-Control-Allow-Origin': '*',
    'Access-Control-Allow-Methods': 'GET',
    'Access-Control-Allow-Headers': 'Content-Type',
    'Access-Control-Max-Age': '3600',
    'User-Agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:52.0) Gecko/20100101 Firefox/52.0'
}
 
url = "http://www.statistics4u.com/fundstat_eng/data_fluriedw.html"
req = requests.get(url, headers)
soup = BeautifulSoup(req.content, 'html.parser')
 
 
data=soup.find('pre').contents[0]
 
str_object = StringIO(data)
 
df = pd.read_csv(str_object,engine='python',skiprows=5,delim_whitespace=True)
 
# Banknotes BN1 to BN100 are genuine, all others are counterfeit
df['Type'] = 'Counterfeit'
df.loc[df.index[:100], 'Type'] = 'Genuine'
 
print(df)
 
sns.set(style="whitegrid", palette="muted")
 
#df = df[['Left', 'Diagonal', 'Type']]
df = pd.melt(df, "Type", var_name="Variable")
 
sp = sns.stripplot(x="value", 
              y="Variable", 
              hue="Type",
              data=df, 
              dodge=True, 
              alpha=.75, 
              zorder=1)
 
#sp.set(xlim=(127, 143)) 
 
sp.legend_.remove()
plt.show()