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Ahmad Radhy
Published © GPL3+

Internet of Things and Data Analytics in Chili Plantation

Get detailed topographic information, fertility rates, homogeneity to soil temperature, and even measure weather in real-time.

AdvancedFull instructions providedOver 2 days1,955
Internet of Things and Data Analytics in Chili Plantation

Things used in this project

Story

Read more

Schematics

Scematic System

smart sensor

Code

air and soil sensor

Arduino
The sensor network system consisting of the ESP8266 microcontroller and the Node-RED programmed in the Linux operating system (OS) on the computer is used to collect data on air temperature, air humidity, light intensity, soil temperature and soil fertility. Sensor data transmission uses Message Queuing Telemetry Transport (MQTT) type protocol to a gateway programmed using Node-RED. By using the MQTT protocol, communication between the microcontroller and mobile apps or computers can be done wirelessly.
#include <PubSubClient.h>
#include <ESP8266WiFi.h>
#include <Adafruit_Sensor.h>
#include <DHT.h>
#include <Wire.h>
#include <BH1750.h>
#include<OneWire.h>
#include<DallasTemperature.h>

//library JSON

#define DHTPIN D5
#define DHTTYPE DHT22
#define ONE_WIRE_BUS D4

OneWire oneWire(ONE_WIRE_BUS);
DallasTemperature sensors(&oneWire);

const char* ssid = "";
const char* password = "";
const char* mqtt_server = "";


WiFiClient espClient;
PubSubClient client(espClient);
long lastData = 0;
DHT dht(DHTPIN, DHTTYPE);
BH1750 lightMeter;


void setup_wifi() {

  delay(10);
  Serial.println();
  Serial.print("Connecting to ");
  Serial.println(ssid);
  //WiFi.mode(WIFI_STA);
  WiFi.begin(ssid, password);

  while (WiFi.status() != WL_CONNECTED) {
    delay(500);
    Serial.print(".");
  }

  randomSeed(micros());

  Serial.println("");
  Serial.println("WiFi connected");
  Serial.println("IP address: ");
  Serial.println(WiFi.localIP());
}

void callback(char* topic, byte* payload, unsigned int length) {

  Serial.print("Message arrived [");
  Serial.print(topic);
  Serial.print("] ");

  for (int i = 0; i < length; i++) {

    Serial.print((char)payload[i]);
  }
  Serial.println();


  if ((char)payload[0] == '1') {
    //digitalWrite(D2, HIGH);

  }

  if((char)payload[0] == '0'){
    
    //digitalWrite(D2, LOW);
  }

}

void reconnect() {

  while (!client.connected()) {

    Serial.print("Attempting MQTT connection...");
    String clientId = "ESP8266Client-";
    clientId += String(random(0xffff), HEX); 

    if (client.connect(clientId.c_str())) { 

      Serial.println("connected");
      //client.publish("output/bacaSensor", "sensor value");
      client.subscribe("input/kendaliAktuator");

    } else {
      
      Serial.print("failed, rc=");
      Serial.print(client.state());
      Serial.println(" try again in 5 seconds");

      delay(5000);
      
    }
  }
}

void setup() {

  pinMode(D5, OUTPUT);
  Serial.begin(9600);
  dht.begin();
  Wire.begin();
  lightMeter.begin();
  sensors.begin();
  setup_wifi();
  client.setServer(mqtt_server, 1883);
  client.setCallback(callback);
}

void loop() {

  if (!client.connected()) {
    
    reconnect();
  }

  client.loop();

  float h = dht.readTemperature();
  float t = dht.readHumidity();
  
  if(isnan(h) || isnan(t)){

    Serial.println("Failed to read from DHT sensor");
    return;
  } 
  
  float tS = sensors.getTempCByIndex(0);
  float l = lightMeter.readLightLevel();
  int adcSoil = analogRead(A0);
  sensors.requestTemperatures();
  float soilHumidity = 0;
  soilHumidity = ((1023.0 - adcSoil)/1023.0)*100;
  
  String temperature = String(t);
  String humidity = String(h);
  String intensity = String(l);
  String soilTemp = String(tS);
  String soilMoisture = String(soilHumidity);
  
  
  String payload = "{\"airTemperature\":";
  payload += temperature;
  payload += ",\"airHumidity\":";
  payload += humidity;
  payload += ",\"intensity\":";
  payload += intensity;
  payload += ",\"soilTemperature\":";
  payload += soilTemp;
  payload += ",\"soilMoisture\":";
  payload += soilMoisture;
  payload += "}";
  
  char dataSensor[250];
  
  long now = millis();

  if (now - lastData > 15000) {

    lastData = now;
    payload.toCharArray(dataSensor, 250);
    client.publish("output/bacaSensor", dataSensor);
    Serial.println(dataSensor);

   
  }
}

data analysis

Python
# Get this figure: fig = py.get_figure("https://plot.ly/~widya.meiriska/35/")
# Get this figure's data: data = py.get_figure("https://plot.ly/~widya.meiriska/35/").get_data()
# Add data to this figure: py.plot(Data([Scatter(x=[1, 2], y=[2, 3])]), filename ="all in", fileopt="extend")
# Get y data of first trace: y1 = py.get_figure("https://plot.ly/~widya.meiriska/35/").get_data()[0]["y"]

# Get figure documentation: https://plot.ly/python/get-requests/
# Add data documentation: https://plot.ly/python/file-options/

# If you're using unicode in your file, you may need to specify the encoding.
# You can reproduce this figure in Python with the following code!

# Learn about API authentication here: https://plot.ly/python/getting-started
# Find your api_key here: https://plot.ly/settings/api

import plotly.plotly as py
from plotly.graph_objs import *
py.sign_in('username', 'api_key')
trace1 = {
  "x": ["8/15/2018 10:38:00.710000000 AM", "8/15/2018 10:38:22.330000000 AM", "8/15/2018 10:38:43.950000000 AM", "8/15/2018 10:39:05.570000000 AM", "8/15/2018 10:39:27.190000000 AM", "8/15/2018 10:39:48.810000000 AM", "8/15/2018 10:39:59.620000000 AM", "8/15/2018 10:40:21.240000000 AM", "8/15/2018 10:40:42.860000000 AM", "8/15/2018 10:41:04.480000000 AM", "8/15/2018 10:41:26.100000000 AM", "8/15/2018 10:41:47.720000000 AM", "8/15/2018 10:42:09.340000000 AM", "8/15/2018 10:42:20.150000000 AM", "8/15/2018 10:42:41.770000000 AM", "8/15/2018 10:43:03.390000000 AM", "8/15/2018 10:43:25.010000000 AM", "8/15/2018 10:43:46.630000000 AM", "8/15/2018 10:44:08.250000000 AM", "8/15/2018 10:44:29.870000000 AM", "8/15/2018 10:44:40.680000000 AM", "8/15/2018 10:45:02.300000000 AM", "8/15/2018 10:45:23.920000000 AM", "8/15/2018 10:45:45.540000000 AM", "8/15/2018 10:46:07.160000000 AM", "8/15/2018 10:46:28.780000000 AM", "8/15/2018 10:46:50.400000000 AM", "8/15/2018 10:47:12.020000000 AM", "8/15/2018 10:47:22.830000000 AM", "8/15/2018 10:47:44.450000000 AM", "8/15/2018 10:48:06.070000000 AM", "8/15/2018 10:48:27.690000000 AM", "8/15/2018 10:48:49.310000000 AM", "8/15/2018 10:49:10.930000000 AM", "8/15/2018 10:49:32.550000000 AM", "8/15/2018 10:49:54.170000000 AM", "8/15/2018 10:50:37.410000000 AM", "8/15/2018 10:50:48.220000000 AM", "8/15/2018 10:51:09.840000000 AM", "8/15/2018 10:51:31.460000000 AM", "8/15/2018 10:51:53.080000000 AM", "8/15/2018 10:52:14.700000000 AM", "8/15/2018 10:52:36.320000000 AM", "8/15/2018 10:52:57.940000000 AM", "8/15/2018 10:53:08.750000000 AM", "8/15/2018 10:53:30.370000000 AM", "8/15/2018 10:53:51.990000000 AM", "8/15/2018 10:54:13.610000000 AM", "8/15/2018 10:54:35.230000000 AM", "8/15/2018 10:54:56.850000000 AM", "8/15/2018 10:55:18.470000000 AM", "8/15/2018 10:55:29.280000000 AM", "8/15/2018 10:55:50.900000000 AM", "8/15/2018 10:56:12.520000000 AM", "8/15/2018 10:56:34.140000000 AM", "8/15/2018 10:56:55.760000000 AM", "8/15/2018 10:57:17.380000000 AM", "8/15/2018 10:57:39.000000000 AM", "8/15/2018 10:58:00.620000000 AM", "8/15/2018 10:58:11.430000000 AM", "8/15/2018 10:58:33.050000000 AM", "8/15/2018 10:58:54.670000000 AM", "8/15/2018 10:59:16.290000000 AM", "8/15/2018 10:59:37.910000000 AM", "8/15/2018 10:59:59.530000000 AM", "8/15/2018 11:00:21.150000000 AM", "8/15/2018 11:00:31.960000000 AM", "8/15/2018 11:00:53.580000000 AM", "8/15/2018 11:01:15.200000000 AM", "8/15/2018 11:01:36.820000000 AM", "8/15/2018 11:01:58.440000000 AM", "8/15/2018 11:02:20.060000000 AM", "8/15/2018 11:02:41.680000000 AM", "8/15/2018 11:02:52.490000000 AM", "8/15/2018 11:03:14.110000000 AM", "8/15/2018 11:03:35.730000000 AM", "8/15/2018 11:03:57.350000000 AM", "8/15/2018 11:04:18.970000000 AM", "8/15/2018 11:04:40.590000000 AM", "8/15/2018 11:05:02.210000000 AM", "8/15/2018 11:05:23.830000000 AM", "8/15/2018 11:05:34.640000000 AM", "8/15/2018 11:05:56.260000000 AM", "8/15/2018 11:06:17.880000000 AM", "8/15/2018 11:06:39.500000000 AM", "8/15/2018 11:07:01.120000000 AM", "8/15/2018 11:07:22.740000000 AM", "8/15/2018 11:07:44.360000000 AM", "8/15/2018 11:07:55.170000000 AM", "8/15/2018 11:08:16.790000000 AM", "8/15/2018 11:08:38.410000000 AM", "8/15/2018 11:09:00.030000000 AM", "8/15/2018 11:09:21.650000000 AM", "8/15/2018 11:09:43.270000000 AM", "8/15/2018 11:10:04.890000000 AM", "8/15/2018 11:10:15.700000000 AM", "8/15/2018 11:10:37.320000000 AM", "8/15/2018 11:10:58.940000000 AM", "8/15/2018 11:11:20.560000000 AM", "8/15/2018 11:11:42.180000000 AM", "8/15/2018 11:12:03.800000000 AM", "8/15/2018 11:12:25.420000000 AM", "8/15/2018 11:12:47.040000000 AM", "8/15/2018 11:12:57.850000000 AM", "8/15/2018 11:13:19.470000000 AM", "8/15/2018 11:13:41.090000000 AM", "8/15/2018 11:14:02.710000000 AM", "8/15/2018 11:14:24.330000000 AM", "8/15/2018 11:14:45.950000000 AM", "8/15/2018 11:15:07.570000000 AM", "8/15/2018 11:15:18.380000000 AM", "8/15/2018 11:15:40.000000000 AM", "8/15/2018 11:16:01.620000000 AM", "8/15/2018 11:16:23.240000000 AM", "8/15/2018 11:16:44.860000000 AM", "8/15/2018 11:17:06.480000000 AM", "8/15/2018 11:17:28.100000000 AM", "8/15/2018 11:17:38.910000000 AM", "8/15/2018 11:18:00.530000000 AM", "8/15/2018 11:18:22.150000000 AM", "8/15/2018 11:18:43.770000000 AM", "8/15/2018 11:19:05.390000000 AM", "8/15/2018 11:19:27.010000000 AM", "8/15/2018 11:19:48.630000000 AM", "8/15/2018 11:19:59.440000000 AM", "8/15/2018 11:20:21.060000000 AM", "8/15/2018 11:20:42.680000000 AM", "8/15/2018 11:21:04.300000000 AM", "8/15/2018 11:21:25.920000000 AM", "8/15/2018 11:21:47.540000000 AM", "8/15/2018 11:22:09.160000000 AM", "8/15/2018 11:22:19.970000000 AM", "8/15/2018 11:22:41.590000000 AM", "8/15/2018 11:23:03.210000000 AM", "8/15/2018 11:23:24.830000000 AM", "8/15/2018 11:23:46.450000000 AM", "8/15/2018 11:24:08.070000000 AM", "8/15/2018 11:24:29.690000000 AM", "8/15/2018 11:24:40.500000000 AM", "8/15/2018 11:25:02.120000000 AM", "8/15/2018 11:25:23.740000000 AM", "8/15/2018 11:25:45.360000000 AM", "8/15/2018 11:26:06.980000000 AM", "8/15/2018 11:26:28.600000000 AM", "8/15/2018 11:26:50.220000000 AM", "8/15/2018 11:27:01.030000000 AM", "8/15/2018 11:27:22.650000000 AM", "8/15/2018 11:27:44.270000000 AM", "8/15/2018 11:28:05.890000000 AM", "8/15/2018 11:28:27.510000000 AM", "8/15/2018 11:28:49.130000000 AM", "8/15/2018 11:29:10.750000000 AM", "8/15/2018 11:29:32.370000000 AM", "8/15/2018 11:29:43.180000000 AM", "8/15/2018 11:30:04.800000000 AM", "8/15/2018 11:30:26.420000000 AM", "8/15/2018 11:30:48.040000000 AM", "8/15/2018 11:31:09.660000000 AM", "8/15/2018 11:31:31.280000000 AM", "8/15/2018 11:31:52.900000000 AM", "8/15/2018 11:32:03.710000000 AM", "8/15/2018 11:32:25.330000000 AM", "8/15/2018 11:32:46.950000000 AM", "8/15/2018 11:33:08.570000000 AM", "8/15/2018 11:33:30.190000000 AM", "8/15/2018 11:33:51.810000000 AM", "8/15/2018 11:34:13.430000000 AM", "8/15/2018 11:34:35.050000000 AM", "8/15/2018 11:34:45.860000000 AM", "8/15/2018 11:35:07.480000000 AM", "8/15/2018 11:35:29.100000000 AM", "8/15/2018 11:35:50.720000000 AM", "8/15/2018 11:36:12.340000000 AM", "8/15/2018 11:36:33.960000000 AM", "8/15/2018 11:36:55.580000000 AM"], 
  "y": ["53.7", "52.1", "49.5", "46.8", "45.9", "46.8", "44.5", "43.1", "42.9", "40.7", "40.7", "40.1", "38.8", "39.2", "39.8", "40.1", "41.8", "40.2", "37.5", "39.2", "38.6", "39.3", "36.8", "37.1", "38.8", "39.1", "39.3", "39.1", "39.6", "41.2", "43.1", "44.5", "45.4", "47.3", "49.4", "51", "52.9", "51.9", "53.8", "54.5", "53.7", "53.1", "53.5", "53.5", "53.8", "55", "56.6", "56.6", "56.5", "56.7", "57.7", "57.6", "57.1", "58.3", "58.5", "58.3", "58.9", "58.1", "59", "59.5", "59.1", "60.2", "61.1", "65.1", "64.1", "63", "60", "62.7", "58.9", "57.3", "55.8", "56.5", "57.4", "59.2", "58.7", "58.8", "56.4", "54.5", "53.2", "52.5", "54.6", "54.7", "55", "54", "55.2", "53.9", "53.7", "54.5", "54.5", "57.5", "56", "54", "55.1", "54.7", "51.8", "51.3", "51.3", "53.6", "52.7", "52.9", "53", "54", "55.9", "56.7", "55.7", "55.4", "55.7", "56.3", "56", "56.1", "55.6", "55.3", "55.8", "55.1", "56.3", "55.6", "55.2", "55.4", "56", "54.8", "54.6", "54", "53.2", "52.6", "52.9", "52.6", "52.6", "53.1", "52.6", "51.8", "51.6", "52.2", "51.3", "51.8", "53", "52.4", "52.7", "51.9", "51.4", "52.6", "52.7", "53.8", "54.5", "54.6", "56.8", "56", "55.7", "55.2", "54.5", "54.1", "53.3", "53.8", "53.8", "55.2", "55.5", "55.9", "54.8", "55.5", "55.8", "57.1", "58.8", "62.4", "59.6", "57.6", "56.4", "56.2", "56.7", "56.5", "55.9", "56.7", "57.5", "57.9", "58.7", "58.4", "58.8"], 
  "mode": "lines", 
  "name": "Kelembaban udara ke 1", 
  "type": "scatter", 
  "xsrc": "widya.meiriska:32:f5f5ce", 
  "ysrc": "widya.meiriska:32:5e5dea"
}
trace2 = {
  "x": ["8/15/2018 10:38:00.710000000 AM", "8/15/2018 10:38:22.330000000 AM", "8/15/2018 10:38:43.950000000 AM", "8/15/2018 10:39:05.570000000 AM", "8/15/2018 10:39:27.190000000 AM", "8/15/2018 10:39:48.810000000 AM", "8/15/2018 10:39:59.620000000 AM", "8/15/2018 10:40:21.240000000 AM", "8/15/2018 10:40:42.860000000 AM", "8/15/2018 10:41:04.480000000 AM", "8/15/2018 10:41:26.100000000 AM", "8/15/2018 10:41:47.720000000 AM", "8/15/2018 10:42:09.340000000 AM", "8/15/2018 10:42:20.150000000 AM", "8/15/2018 10:42:41.770000000 AM", "8/15/2018 10:43:03.390000000 AM", "8/15/2018 10:43:25.010000000 AM", "8/15/2018 10:43:46.630000000 AM", "8/15/2018 10:44:08.250000000 AM", "8/15/2018 10:44:29.870000000 AM", "8/15/2018 10:44:40.680000000 AM", "8/15/2018 10:45:02.300000000 AM", "8/15/2018 10:45:23.920000000 AM", "8/15/2018 10:45:45.540000000 AM", "8/15/2018 10:46:07.160000000 AM", "8/15/2018 10:46:28.780000000 AM", "8/15/2018 10:46:50.400000000 AM", "8/15/2018 10:47:12.020000000 AM", "8/15/2018 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  "y": ["20.88", "20.88", "20.88", "20.88", "20.88", "20.88", "20.94", "20.94", "20.94", "20.94", "20.94", "20.94", "20.94", "20.94", "20.94", "20.94", "21", "21", "21", "21", "21", "21", "21", "21.03", "21.06", "21.06", "21.06", "21.06", "21.06", "21.06", "21.06", "21.12", "21.09", "21.12", "21.12", "21.12", "21.12", "21.12", "21.19", "21.19", "21.19", "21.19", "21.19", "21.19", "21.19", "21.19", "21.19", "21.25", "21.25", "21.25", "21.25", "21.25", "21.25", "21.25", "21.28", "21.31", "21.31", "21.31", "21.31", "21.31", "21.34", "21.31", "21.37", "21.37", "21.37", "21.37", "21.37", "21.37", "21.37", "21.37", "21.37", "21.37", "21.37", "21.44", "21.44", "21.37", "21.44", "21.44", "21.44", "21.44", "21.44", "21.44", "21.44", "21.44", "21.44", "21.5", "21.47", "21.5", "21.5", "21.5", "21.5", "21.5", "21.5", "21.5", "21.5", "21.5", "21.53", "21.56", "21.56", "21.56", "21.56", "21.56", "21.56", "21.56", "21.59", "21.62", "21.62", "21.62", "21.62", "21.62", "21.62", "21.62", "21.69", "21.655", "21.655", "21.69", "21.69", "21.69", "21.69", "21.69", "21.69", "21.69", "21.75", "21.75", "21.75", "21.75", "21.75", "21.75", "21.75", "21.78", "21.78", "21.81", "21.81", "21.81", "21.81", "21.81", "21.81", "21.81", "21.81", "21.81", "21.84", "21.81", "21.81", "21.87", "21.87", "21.87", "21.87", "21.87", "21.87", "21.87", "21.87", "21.87", "21.87", "21.87", "21.87", "21.87", "21.87", "21.87", "21.87", "21.87", "21.905", "21.905", "21.94", "21.94", "21.94", "21.94", "21.94", "21.94", "21.94", "21.94", "21.94", "22", "22", "22", "22", "22", "22", "22", "22", "22", "22", "22", "22", "22", "22.03", "22.03", "22.06", "22.03", "22.06", "22.06", "22.06", "22.06", "22.06", "22.06", "22.06", "22.06", "22.06", "22.06", "22.06", "22.06", "22.06", "22.06", "22.06", "22.06", "22.06", "22.13", "22.13", "22.13", "22.13", "22.13", "22.13", "22.13", "22.13", "22.13", "22.19", "22.16", "22.19", "22.19", "22.19", "22.19", "22.19", "22.19", "22.19", "22.22", "22.25", "22.25", "22.25", "22.25", "22.25", "22.25", "22.25", "22.25", "22.25", "22.25", "22.25", "22.25", "22.31", "22.31", "22.31", "22.31", "22.31", "22.31", "22.31", "22.31", "22.31", "22.31", "22.31", "22.31", "22.31", "22.31", "22.31", "22.34", "22.34", "22.37", "22.37", "22.37", "22.37", "22.37", "22.37", "22.37", "22.405", "22.44", "22.44", "22.44", "22.44", "22.44", "22.44", "22.44", "22.44", "22.44", "22.5", "22.5", "22.5", "22.5", "22.5", "22.5", "22.5", "22.5", "22.5", "22.5", "22.5", "22.53", "22.56", "22.56", "22.56", "22.56", "22.56", "22.56", "22.56", "22.56", "22.56", "22.56", "22.56", "22.56", "22.62", "22.59", "22.62", "22.62", "22.62", "22.62", "22.62", "22.62", "22.62", "22.62", "22.62", "22.62", "22.655", "22.69", "22.655", "22.69", "22.69", "22.69", "22.69", "22.69", "22.69", "22.69", "22.72", "22.75", "22.75", "22.75", "22.75", "22.75", "22.75", "22.75", "22.75", "22.75", "22.75", "22.75", "22.78", "22.81", "22.81", "22.81", "22.81", "22.81"], 
  "line": {
    "color": "rgb(255, 127, 14)", 
    "dash": "dot"
  }, 
  "mode": "lines", 
  "name": "Temperatur tanah hari ke 3", 
  "type": "scatter", 
  "xsrc": "widya.meiriska:34:4399bc", 
  "ysrc": "widya.meiriska:34:63c6fb"
}
data = Data([trace1, trace2, trace3, trace4, trace5, trace6, trace7, trace8, trace9, trace10, trace11, trace12, trace13, trace14, trace15])
layout = {
  "autosize": False, 
  "height": 700, 
  "hovermode": "closest", 
  "margin": {"b": 100}, 
  "showlegend": True, 
  "title": "<b>Monitoring Data Tanaman Cabe di Balitsa</b>", 
  "titlefont": {"size": 18}, 
  "width": 1200, 
  "xaxis": {
    "autorange": True, 
    "nticks": -1, 
    "range": [0, 810], 
    "tickangle": "auto", 
    "title": "<b>Waktu</b>", 
    "type": "category"
  }, 
  "yaxis": {
    "autorange": True, 
    "range": [1.78566666667, 68.4323333333], 
    "title": "<b>Nilai yang terukur</b>", 
    "type": "linear"
  }
}
fig = Figure(data=data, layout=layout)
plot_url = py.plot(fig)

histogram

Python
# Get this figure: fig = py.get_figure("https://plot.ly/~widya.meiriska/2/")
# Get this figure's data: data = py.get_figure("https://plot.ly/~widya.meiriska/2/").get_data()
# Add data to this figure: py.plot(Data([Scatter(x=[1, 2], y=[2, 3])]), filename ="humidity", fileopt="extend")
# Get x data of first trace: x1 = py.get_figure("https://plot.ly/~widya.meiriska/2/").get_data()[0]["x"]

# Get figure documentation: https://plot.ly/python/get-requests/
# Add data documentation: https://plot.ly/python/file-options/

# If you're using unicode in your file, you may need to specify the encoding.
# You can reproduce this figure in Python with the following code!

# Learn about API authentication here: https://plot.ly/python/getting-started
# Find your api_key here: https://plot.ly/settings/api

import plotly.plotly as py
from plotly.graph_objs import *
py.sign_in('username', 'api_key')
trace1 = {
  "x": [53.7, 52.1, 49.5, 46.8, 45.9, 46.8, 44.5, 43.1, 42.9, 40.7, 40.7, 40.1, 38.8, 39.2, 39.8, 40.1, 41.8, 40.2, 37.5, 39.2, 38.6, 39.3, 36.8, 37.1, 38.8, 39.1, 39.3, 39.1, 39.6, 41.2, 43.1, 44.5, 45.4, 47.3, 49.4, 51, 52.9, 51.9, 53.8, 54.5, 53.7, 53.1, 53.5, 53.5, 53.8, 55, 56.6, 56.6, 56.5, 56.7, 57.7, 57.6, 57.1, 58.3, 58.5, 58.3, 58.9, 58.1, 59, 59.5, 59.1, 60.2, 61.1, 65.1, 64.1, 63, 60, 62.7, 58.9, 57.3, 55.8, 56.5, 57.4, 59.2, 58.7, 58.8, 56.4, 54.5, 53.2, 52.5, 54.6, 54.7, 55, 54, 55.2, 53.9, 53.7, 54.5, 54.5, 57.5, 56, 54, 55.1, 54.7, 51.8, 51.3, 51.3, 53.6, 52.7, 52.9, 53, 54, 55.9, 56.7, 55.7, 55.4, 55.7, 56.3, 56, 56.1, 55.6, 55.3, 55.8, 55.1, 56.3, 55.6, 55.2, 55.4, 56, 54.8, 54.6, 54, 53.2, 52.6, 52.9, 52.6, 52.6, 53.1, 52.6, 51.8, 51.6, 52.2, 51.3, 51.8, 53, 52.4, 52.7, 51.9, 51.4, 52.6, 52.7, 53.8, 54.5, 54.6, 56.8, 56, 55.7, 55.2, 54.5, 54.1, 53.3, 53.8, 53.8, 55.2, 55.5, 55.9, 54.8, 55.5, 55.8, 57.1, 58.8, 62.4, 59.6, 57.6, 56.4, 56.2, 56.7, 56.5, 55.9, 56.7, 57.5, 57.9, 58.7, 58.4, 58.8], 
  "autobinx": True, 
  "autobiny": True, 
  "name": "Hari ke 1", 
  "opacity": 0.75, 
  "type": "histogram", 
  "uid": "9c4ed06a-aa95-11e8-ba3f-c4461925a71b", 
  "xbins": {
    "end": 66, 
    "size": 2, 
    "start": 36
  }, 
  "xsrc": "widya.meiriska:3:84dd94"
}
trace2 = {
  "x": [34.7, 35.05, 35.15, 36, 36.15, 35.45, 34.25, 33.75, 34.5333333333, 33.6, 33.6, 34, 33.8, 34.95, 35.2, 34.8, 33.95, 32.45, 32.55, 31.9, 30.85, 30.6, 31.35, 31.4, 32.1333333333, 31.6, 31.1, 31.8, 31.4, 31.1, 30.3, 30.3, 30.4, 30.75, 31.7, 31.35, 31.45, 30.7, 30.45, 31.45, 32.2, 33.85, 34.05, 34.55, 34.6, 34, 34.1, 33.8666666667, 33.05, 32.6, 33.6, 34.9333333333, 35.7, 33.4333333333, 33.8, 33.4, 33.75, 33.3, 33.1, 33.8, 34.3, 34.9, 35.85, 36.3, 35.95, 37.4, 38.05, 37.95, 37.8, 37.7, 38.9, 39.95, 39.9, 41.25, 41.5, 41.8, 42.3, 42.4, 42.8, 42.5, 43.1, 43.6, 43.5, 43.45, 43.45, 43.75, 43.8, 43.65, 42.6, 41.8, 41.6, 43.4, 45.3, 46.1, 44.45, 44.9, 44.5, 43.55, 41.75, 41.1, 41.6, 42.7, 43.55, 44, 42.45, 40.5, 40.3, 39, 36.85, 36.4666666667, 37, 36, 35.7, 37.05, 37.05, 37, 35.15, 35.15, 35.2, 35.9, 34.85, 34.55, 34.7, 34.9, 36.9, 37.4, 37.65, 37.05, 36.25, 38.2, 40.05, 39.7, 40.3666666667, 41.9, 42.15, 42.55, 42.35, 42.6, 42.8, 43.2, 43.95, 45.5, 46.45, 46.65, 46.65, 47.45, 48.8, 49.1, 49.85, 50.15, 51.25, 52.6666666667, 52.7, 53.7, 53.8, 54.15, 54.5, 55, 55.55, 56, 56.2333333333, 56.7, 57.35, 57.5, 57.75, 58.05, 58.25, 59, 59.8, 59.75, 60, 60.1, 60.4, 60.9, 60.3, 59.5, 57.65, 56.95, 57.3, 56.4, 56.65, 56.7, 57.3333333333, 57.5, 58.1, 57.1, 56.8, 57.2, 57.7, 57.4, 57.75, 58.2, 58.45, 58.85, 59.6, 60.55, 60, 59.35, 60.5, 60.85, 62.1, 61, 61.05, 61.9, 62, 61.8, 61.9, 60.75, 60.4, 60.55, 61.85, 61.8, 62, 62.55, 60.8, 62.35, 60.6, 60.1, 59.45, 55.6, 54.9, 53.65, 52.6666666667, 52.5666666667, 55.1666666667, 55.25, 54.9, 55.25, 56, 56.3, 54.3, 53.7, 53.55, 52.1, 52.35, 54.75, 56.45, 57.3, 56.4, 56.55, 57.2, 56.05, 55.2, 56.1, 55.75, 53.95, 51.5, 51.9, 52.15, 50.75, 50.15, 50.4, 50.5, 47.5, 46.8, 47.2, 46.4, 45.8, 43.5, 43.1, 42.5333333333, 44.75, 44.95, 44.4, 44.25, 43.05, 41.2, 41.14, 40.75, 39.2, 39.2, 39, 39.8, 39.8, 40.05, 39.9333333333, 39.75, 40.35, 40.1, 40.15, 40.3, 38.95, 39.3, 38.6, 37.85, 38.1, 37.7, 37.4, 38.6666666667, 39, 38.15, 38.1, 38.6, 38.5, 37.8, 38.6, 37.4, 37.65, 37.9, 36.55, 37.1, 37.5], 
  "autobinx": True, 
  "autobiny": True, 
  "name": "Hari ke 2", 
  "opacity": 0.75, 
  "type": "histogram", 
  "uid": "9c4ed06b-aa95-11e8-ba3f-c4461925a71b", 
  "xbins": {
    "end": 65, 
    "size": 5, 
    "start": 30
  }, 
  "xsrc": "widya.meiriska:3:87d54f"
}
trace3 = {
  "x": [29, 28.55, 27.35, 26.2, 25.75, 25.3, 25.05, 24.7, 24.95, 24.9, 26.45, 26.35, 29.15, 30.95, 31.7, 32.2333333333, 33, 33.1, 32.2, 31.95, 31.95, 31.75, 32.05, 32.25, 31.9, 31.35, 29.95, 28.9, 29.65, 30.15, 31.1, 32.0666666667, 31, 30.15, 29.55, 29.6, 29.75, 29.75, 30.55, 31.05, 31.1, 30.55, 31.05, 31.3, 31.2, 31.45, 28, 26.15, 25.85, 25.3, 26.2, 26.9, 27, 27.05, 26.4, 27.1, 29.4, 30.1, 29.7, 31.4, 32, 32.3, 31.65, 32.35, 32.75, 31.8, 31.15, 30.65, 29.85, 27.9, 27.05, 26.35, 26.4, 27.25, 26.75, 26.2, 27.75, 29.15, 29.3, 28.7, 27.75, 26.8, 26.7, 26, 24.85, 24.55, 24.55, 24.8, 25.05, 25.5, 25.95, 26.45, 26.85, 26.9, 27.2, 27.45, 27.25, 27, 27.05, 26.85, 27.5, 27.75, 27.8, 27.6, 27.15, 26.9, 26.8666666667, 26.3, 26.45, 26, 25.8, 26.6, 26.7, 27.15, 27.3, 27.45, 27.7, 28.35, 29.35, 30.85, 31.85, 32.8, 32.75, 32.7, 32.35, 32, 32.4, 31.9, 31.7, 31.3, 30.2, 29.05, 28.85, 28.65, 28.75, 28.95, 28.8, 28.8, 29, 28.5, 28.4, 29.1, 30.25, 30.4, 30.15, 30.1, 28.95, 27.75, 27.7, 27.85, 27.55, 27.65, 28.1, 28.15, 28.4, 28.35, 28.25, 28, 28.05, 27.95, 28.2, 29, 28.8, 29.2, 29.1, 28.9, 27.8, 27.2, 26.95, 27.35, 27.35, 27.25, 27.1, 27.8, 28.2, 28.5, 28.65, 28.55, 27.4, 26.8, 26.7, 27.15, 27.3, 27.3, 26.95, 26, 25.4, 25.15, 24.6, 24.25, 24.65, 25.45, 25.75, 25.3, 25.75, 25.6, 25.35, 25.5, 25.3, 25.3, 25.4, 25.75, 26.5, 27.5, 29.05, 29, 29.1, 29.2, 28.55, 28.15, 28.6, 29.6, 30.55, 32, 32.5, 32.15, 31.9, 30.9, 30.45, 30.4, 30.1, 29.75, 29.7, 29.45, 29.4, 28.7, 27.6, 27.2, 27.05, 27.2, 27.5, 27.75, 27.5, 26.1, 26.2, 24.75, 23.75, 23.3, 23.3, 22.95, 23.15, 23.6, 23.85, 23.65, 24.3, 25.6, 26.4, 26.7, 25.25, 24.5, 25.4, 25.8, 26.15, 26.65, 26.5, 27.15, 26.05, 25.9, 26.85, 26.95, 27.95, 27.9, 28.65, 28.4, 28.6, 28.6, 28.2, 27.4, 28.15, 28.15, 28.15, 28.7, 28.75, 29.25, 30.05, 29.7, 29.55, 29.45, 28.25, 27.95, 27.75, 28.15, 28, 28.5, 27.85, 27.05, 26.3, 26.9, 28, 26.65, 27.05, 26.8, 27, 28.75, 29.05, 29.4, 29.1, 28.45, 28.25, 27.7, 27.05, 27.35, 27.6, 27.65, 27.15, 27.7, 27.6, 27.45, 27.15, 26.85, 27.15, 27.7333333333, 26.7, 26.5, 26.2, 25.75, 25.65, 25.8, 25.85, 25.4, 25.15, 25.55, 25.4, 26.3, 26.15, 26.35, 27.1, 27.2, 28.2, 29.05, 27.7, 27.1, 27.35, 27.6], 
  "autobinx": True, 
  "autobiny": True, 
  "name": "Hari ke 3", 
  "opacity": 0.75, 
  "type": "histogram", 
  "uid": "9c4ed06c-aa95-11e8-ba3f-c4461925a71b", 
  "xbins": {
    "end": 33.5, 
    "size": 0.5, 
    "start": 22.5
  }, 
  "xsrc": "widya.meiriska:3:3cc987"
}
data = Data([trace1, trace2, trace3])
layout = {
  "barmode": "overlay", 
  "dragmode": "pan", 
  "legend": {
    "x": 1.00476454294, 
    "y": 0.538235294118
  }, 
  "title": "&nbsp;&lt;b&gt;Persebaran Nilai Kelembaban Udara pada Tanaman Cabai di Balitsa&lt;/b&gt;&nbsp;", 
  "titlefont": {"size": 18}, 
  "xaxis": {
    "autorange": True, 
    "range": [22.5, 66], 
    "title": "<b>Kelembaban Udara</b>", 
    "type": "linear"
  }, 
  "yaxis": {
    "autorange": True, 
    "range": [0, 69.4736842105], 
    "title": "<b>Frekuensi</b>"
  }
}
fig = Figure(data=data, layout=layout)
plot_url = py.plot(fig)

Credits

Ahmad Radhy

Ahmad Radhy

24 projects • 46 followers
Physicist and IoT Software and Hardware Engineer
Thanks to Dr.rer.nat. Sparisoma Viridi and Drs. Maman Budiman, Ph.D.

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