Ahmad RadhyWidya Meiriska
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 days410
Internet of Things and Data Analytics in Chili Plantation

Things used in this project

Hardware components

Wemos D1 Mini
Espressif Wemos D1 Mini
×1
Raspberry Pi 3 Model B
Raspberry Pi 3 Model B
×1
DHT22 Temperature Sensor
DHT22 Temperature Sensor
×1
Grove - Light Sensor
Seeed Grove - Light Sensor
×1
DS18B20 Programmable Resolution 1-Wire Digital Thermometer
Maxim Integrated DS18B20 Programmable Resolution 1-Wire Digital Thermometer
×1
SparkFun Soil Moisture Sensor (with Screw Terminals)
SparkFun Soil Moisture Sensor (with Screw Terminals)
×1
Rapid IoT Prototyping Kit
NXP Rapid IoT Prototyping Kit
×1

Software apps and online services

Node-RED
Node-RED
Arduino IDE
Arduino IDE

Story

Read more

Schematics

Scematic System

Model srludaimlf

smart sensor

Whatsapp image 2018 08 28 at 19 40 11 et6p3d4vrh

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 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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 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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 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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

1 project • 5 followers
I'm master student in physics department Institut Teknologi Bandung (ITB)
Widya Meiriska

Widya Meiriska

0 projects • 1 follower
Thanks to Dr.rer.nat. Sparisoma Viridi and Drs. Maman Budiman, Ph.D.

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