haydarai

/* Nyari sekolah yang deket traffic light */
SELECT name, ST_DISTANCE(geom, (SELECT geom from public."traffic lights" WHERE gid = 10))
FROM 
  public."school and universities"
WHERE ST_DISTANCE(geom, (SELECT geom from public."traffic lights" WHERE gid = 10)) < 1000
ORDER BY ST_DISTANCE ASC

haydarai

{
  "Discussion": {
    "DiscussionID": "1",
    "Type": null,
    "ForeignID": "stub",
    "CategoryID": "1",
    "InsertUserID": "2",
    "UpdateUserID": null,
    "FirstCommentID": "1",
    "LastCommentID": "48",

haydarai

ArrayList<int> fibonaccip = new ArrayLiatt<int>();
fibonaccip.add(1);
int ip1 

for (int i = 0; i < n; i++) {
	int ip1;
	if ((i - p - 1) > 0) {
		ip1 = 0;
	} else {
		ip1 = i - p - 1;

haydarai

{
  "data": {
    "paragraphs": [
      {
        "title": "First paragraph",
        "image": "http://pasienia.com/1.jpg",
        "content": "This is first paragraph",
        "list": [
          "This is first point",
          "This is second point",

haydarai

        HttpURLConnection urlConnection = null;
        BufferedReader reader = null;

        String forecastJsonStr = null;

        try {
            String baseUrl = "http://api.openweathermap.org/data/2.5/forecast/daily?q=94043&mode=json&units=metric&cnt=7";
            String apiKey = "&APPID=" + BuildConfig.OPEN_WEATHER_MAP_API_KEY;
            URL url = new URL(baseUrl.concat(apiKey));

haydarai

%matplotlib inline 

import numpy as np
import pandas as pd
import scipy.stats as stats
import matplotlib.pyplot as plt
import sklearn
import statsmodels.api as sm

import seaborn as sns

haydarai

print(boston.feature_names)

haydarai

print(boston.DESCR)

haydarai

print(boston.target.shape)

haydarai

from sklearn.datasets import load_boston
boston = load_boston()