nmoya

(ns advent-of-code.core
  (:gen-class))

(defn next-coordinates [row column max-row]
  (let [new-row (dec row)
        new-column (inc column)]
    (if (< new-row 0)
      [(inc max-row) 0]
      [new-row new-column])))

nmoya

from sklearn.cluster import KMeans
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from PIL import Image
import cv2
import pandas as pd
import numpy as np

def color_fn(values):
    colors = []

nmoya

from sklearn import svm
import pandas as pd
import numpy as np

test = pd.read_csv("./titanic/data/test.csv")
train = pd.read_csv("./titanic/data/train.csv")
drop_columns = ["PassengerId", "Name", "Embarked", "Cabin", "Ticket", "Age", "Fare"]
train_drop_columns = ["Survived"] + drop_columns

# Labels from the training set

nmoya

(ns transducer-meetup.core)


(defn noop [xf]
  (clojure.pprint/pprint (type xf))
  (clojure.pprint/pprint xf)
  (fn
    ([] (xf))
    ([result] (xf result))
    ([result input] (xf result input))))

nmoya

from parse_rest.connection import ParseBatcher
from parse_rest.connection import register
from parse_rest.datatypes import Object
from parse_rest.installation import Push


''' Database helper to interact data with parse.com 
For additional documentation, check: https://github.com/dgrtwo/ParsePy
In order to ease the implementation of this helper, more complex queries
like sorting, should be done in python after retrieving a list of rows.'''