sinhrks

import squarify
import matplotlib.pyplot as plt
from numpy.random import rand

fig, axes = plt.subplots(2, 3, figsize=(14, 8))
plt.subplots_adjust(top=0.95, bottom=0.05, left=0.05, right=0.95, hspace=0.35)

sq = 8

def random_colors(n):

sinhrks

from pandas import Series, DataFrame

import numpy as np
from numpy.random import randn, rand

import pandas.tools.plotting as plotting
import matplotlib.pyplot as plt

s = Series(randn(6), index=range(6))

sinhrks

# -*- coding: utf-8 -*-
"""
This code uses "MLP" class defined in:
http://deeplearning.net/tutorial/mlp.html#tips-and-tricks-for-training-mlps
""" 

import os
import sys
import time

sinhrks

library(dplyr)
library(tidyr)
library(ggplot2)
library(gridExtra)
library(animation)

plot_dtw_matrix <- function(ts_a, ts_b, i, j, cost, dist) {
  
  .plot_matrix <- function(m, title, low, high) {
    d <- dplyr::tbl_df(data.frame(m))

sinhrks

# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from collections import defaultdict

import numpy as np
np.random.seed(1)
import networkx as nx

class MRF(object):
    

sinhrks

library(survival)

library(ggplot2)
library(scales)

d.survfit <- survival::survfit(survival::Surv(time, status) ~ sex,
                               data = lung)

fortify.survfit <- function(survfit.data) {
  data.frame(time = survfit.data$time,

sinhrks

sinhrks

目的

• pandas にプルリクエスト (PR) を送りたい

Git/GitHubの設定

• https://employment.en-japan.com/engineerhub/entry/2017/01/31/110000

pandasリポジトリのクローン

sinhrks

import string

from pandas import DataFrame

import numpy as np
from numpy.random import randn

import pandas.tools.plotting as plotting

from matplotlib.pylab import close

sinhrks

#!/bin/bash

# --------------------------------------------------------------------------------------
# Preparation
# To execute this script, please follow:

# wget https://gist.github.com/sinhrks/ba9876e7aa2a18a601f8/raw/environment_setup.sh
# chmod +x environment_setup.sh
# ./environment_setup.sh
# --------------------------------------------------------------------------------------