import pandas as pd
import numpy as np
from tabulate import tabulate
df = pd.DataFrame(np.random.random((4,3)), columns=['A','B','C'])
print("foo")
return(tabulate(df, headers="keys", tablefmt="orgtbl"))
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# Generate data in the form of a sine wave | |
set.seed(1) | |
n <- 1e3 | |
dat <- data.frame( | |
x = 1:n, | |
y = sin(seq(0, 5*pi, length.out = n)) + rnorm(n=n, mean = 0, sd=0.1) | |
) | |
approxData <- data.frame( |
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user nginx; | |
worker_processes 1; | |
error_log /var/log/nginx/error.log warn; | |
pid /var/run/nginx.pid; | |
events { | |
worker_connections 1024; | |
} |
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# Virtual Host configuration for myorg.cl | |
# | |
# You can move that to a different file under sites-available/ and symlink that | |
# to sites-enabled/ to enable it. | |
# | |
server { | |
listen 80; | |
listen 443 ssl; | |
ssl_certificate /etc/letsencrypt/live/myhost.myorg.cl/fullchain.pem; |
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import pyproj | |
def utm2dmh(x, y): | |
"""Transformacion coordenadas WGS84/UTM 19S a DMH""" | |
a1 = 1.01340872464667 | |
b1 = 0.000356424618826433 | |
c1 = -509325.431674420 | |
a2 = -0.00134028501767773 | |
b2 = 1.00293580527335 |
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celda = { | |
fase:"", | |
banco:"", | |
nombre:"", | |
identificador:number, | |
vcelda: [ | |
{ | |
x:1, | |
y:2, |
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# Run as : | |
# docker run -it --rm -e DISPLAY=$DISPLAY --net=host -v /tmp/.X11-unix:/tmp/.X11-unix container-name | |
FROM debian:stretch | |
RUN apt-get -y update && apt-get install -y | |
ENV HOME /home/dbschema | |
ENV USER dbschema |
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import math as m | |
def mlp2sirgas(x_in, y_in): | |
K = 0.9993861340849 | |
W = 0.0025759302920 | |
T_x = 299836.7973 | |
T_y = 6399665.955 | |
teta= W * m.pi / 180.0 |
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import math as m | |
E = 374615.956 | |
N = 6227561.662 | |
R = m.pi * (13 +18.0/60.0 + 19.35/3600.0) / 180 | |
d = 3000; | |
def sirgas2tte(e, n) : | |
tmpE = e - E; |
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