Let your data shine with Dowell Central Tendencies API.
Welcome to the Dowell Central Tendencies for Big Statistical Data API ! This API provides a powerful endpoint to calculate various statistical tendencies for large datasets. It enables users to easily retrieve essential statistical measures such as mean, median, mode, standard deviation, kurtosis, skewness, normal distribution, central moments, and raw moments. With this API, you can analyze and gain insights from your data with ease.
Calculate the average value of a dataset.
Determine the middle value in a sorted dataset.
Identify the most frequently occurring value(s) in a dataset.
Standard Deviation Calculation: Measure the spread or dispersion of data points from the mean.
Determine the shape of the dataset’s distribution and detect heavy tails or outliers.
Compute the asymmetry or lack of symmetry in the dataset’s distribution.
Analyze whether the dataset follows a normal distribution or deviates from it.
Calculate measures providing insights into the shape, symmetry, and kurtosis of the dataset.
Compute measures providing insights into the central tendency and spread of the dataset.
The Central Tendencies for Big Statistical Data API categorizes the results into two groups based on the provided data and calculation methodology:
Please note that the categorization of results into “Poisson Case Results” and “Normal Case Results” allows users to analyze individual datasets separately or obtain overall tendencies for a merged dataset, based on their specific requirements and use cases.
Follow these steps to get started with the Central Tendencies for Big Statistical Data API:
Sign up for an API key at through our website or by getting in toch with our support team to access the API endpoints.
Refer to the API Postman Documentation mention below in for detailed information about available endpoints, request parameters, and response formats.
Make API requests to calculate the desired statistical tendencies for your dataset by providing the necessary parameters and authenticating with your API key.
Analyze and interpret the returned results to gain insights into your data’s central tendencies.
Here are some examples of how you can use the Central Tendencies for Big Statistical Data API:
Calculate the mean, median, and mode of a sales dataset to understand the typical sales figures and most frequently occurring values.
Analyze the standard deviation of stock prices to assess the volatility and risk associated with specific stocks.
Calculate the kurtosis and skewness of customer purchase amounts to identify potential outliers and deviations from a normal distribution.
Compute the central moments and raw moments of a population health dataset to gain insights into its shape, symmetry, and spread.
For detailed API documentation, including endpoint descriptions, request and response examples, and authentication details, please refer to the API documentation
In the following scenarios, Dowell will furnish comprehensive instructions on obtaining the Service key and guide you through the steps to use the API. You’ll find examples in various formats such as Python, PHP, React, Flutter, and WordPress in the tabs below. Feel free to explore the examples in each tab for practical insights.
The API can calculate mean, median, mode, standard deviation, kurtosis, skewness, and analyze normal distributions among other things.
Yes, the API categorizes results into “Poisson Case Results” for individual datasets and “Normal Case Results” for merged datasets.
You need to provide the API key, dataset title, and values for each list within the dataset.
The response headers contain information like success messages, dataset titles, and statistical results for both “Poisson Case” and “Normal Case”.
Moments provide insights into the shape, symmetry, and spread of a dataset.
If you encounter any issues, have questions, or need assistance with Dowell Central Tendencies for Big Statistical Data API, you can contact the support team for prompt assistance. Contact us at Dowell@dowellresearch.uk
Yes, you can retrieve existing data by providing your API key and process ID.
Skewness measures the asymmetry of the dataset’s distribution. Positive skewness indicates a longer tail on the right side, while negative skewness indicates a longer tail on the left side.
Merged results provide insights into overall tendencies when multiple datasets are combined.
Dowell UX Living Lab offers a wide range of APIs to enhance user experience and streamline various processes. To explore the full list of APIs available, including Dowell SMS, Dowell Newsletter, Samanta Content Evaluator, and many more.
For more details and to explore the complete list of APIs provided by Dowell UX Living Lab, please visit our documentation page.
This script sends a POST request to a specified URL with a payload to generate central tendencies. It handles the response, printing success or failure messages along with the response data.
import requests
url = "https://100004.pythonanywhere.com/api"
payload = {
"api_key": "c2636d98-4f43-4be1-9e3b-47cdfcbe832b",
"title": "demo-case4",
"Process_id": 122,
"processSequenceId": 11,
"series": 4,
"seriesvalues": {
"list1": [3, 3, 3, 2, 1, 1, 2, 5, 6, 15],
"list2": [11, 2, 2, 4, 2, 2, 5, 6, 8, 9],
"list3": [9, 2, 3, 3, 4, 4, 4, 7, 8, 9],
"list4": [1, 2, 3, 4, 4, 4, 4, 2, 2, 8],
"list5": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
},
}
try:
response = requests.post(url, json=payload)
if response.status_code == 201:
print("Resource created successfully")
# Optionally, you can also print or process the response data
data = response.json()
print(data)
else:
print(f"Request failed with status code: {response.status_code}")
print(response.text)
except requests.exceptions.RequestException as e:
print(f"Request failed with an exception: {e}")
This script sends a GET request to a specified URL with a payload to view existing data. It handles the response, printing success or failure messages along with the response data.
import requests
url = "https://100004.pythonanywhere.com/api"
payload = {"api_key": "c2636d98-4f43-4be1-9e3b-47cdfcbe832b", "Process_id": 123}
try:
response = requests.get(url, json=payload)
if response.status_code == 201:
print("Resource created successfully")
# Optionally, you can also print or process the response data
data = response.json()
print(data)
else:
print(f"Request failed with status code: {response.status_code}")
print(response.text)
except requests.exceptions.RequestException as e:
print(f"Request failed with an exception: {e}")
This PHP script generates central tendencies by sending a POST request to a specified URL with a payload. It handles the response, printing success or failure messages along with the response data.
"c2636d98-4f43-4be1-9e3b-47cdfcbe832b",
"title" => "demo-case4",
"Process_id" => 122,
"processSequenceId" => 11,
"series" => 4,
"seriesvalues" => array(
"list1" => [3, 3, 3, 2, 1, 1, 2, 5, 6, 15],
"list2" => [11, 2, 2, 4, 2, 2, 5, 6, 8, 9],
"list3" => [9, 2, 3, 3, 4, 4, 4, 7, 8, 9],
"list4" => [1, 2, 3, 4, 4, 4, 4, 2, 2, 8],
"list5" => [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
),
);
$options = array(
'http' => array(
'header' => "Content-type: application/x-www-form-urlencoded\r\n",
'method' => 'POST',
'content' => http_build_query($data),
),
);
$context = stream_context_create($options);
$result = file_get_contents($url, false, $context);
if ($result !== FALSE) {
echo "Resource created successfully\n";
$data = json_decode($result, true);
print_r($data);
} else {
echo "Request failed with an exception: " . error_get_last()['message'];
}
?>
This PHP script views existing data by sending a GET request to a specified URL with a payload. It handles the response, printing success or failure messages along with the response data.
"your_api_key",
"Process_id" => 123,
);
$options = array(
'http' => array(
'header' => "Content-type: application/x-www-form-urlencoded\r\n",
'method' => 'GET',
'content' => http_build_query($data),
),
);
$context = stream_context_create($options);
$result = file_get_contents($url, false, $context);
if ($result !== FALSE) {
echo "Resource retrieved successfully\n";
$data = json_decode($result, true);
print_r($data);
} else {
echo "Request failed with an exception: " . error_get_last()['message'];
}
?>
This React script generates central tendencies by sending a POST request to a specified URL with a payload. It handles the response, logging success or failure messages along with the response data.
import React, { useEffect } from 'react';
const GenerateCentralTendencies = () => {
const url = "https://example.com/api";
const payload = {
api_key: "your_api_key",
title: "demo-case4",
Process_id: 122,
processSequenceId: 11,
series: 4,
seriesvalues: {
list1: [3, 3, 3, 2, 1, 1, 2, 5, 6, 15],
list2: [11, 2, 2, 4, 2, 2, 5, 6, 8, 9],
list3: [9, 2, 3, 3, 4, 4, 4, 7, 8, 9],
list4: [1, 2, 3, 4, 4, 4, 4, 2, 2, 8],
list5: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
},
};
useEffect(() => {
const fetchData = async () => {
try {
const response = await fetch(url, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify(payload),
});
if (response.status === 201) {
console.log("Resource created successfully");
const data = await response.json();
console.log(data);
} else {
console.log(`Request failed with status code: ${response.status}`);
console.log(await response.text());
}
} catch (error) {
console.log(`Request failed with an exception: ${error.message}`);
}
};
fetchData();
}, [url, payload]);
return (
{/* Your React component JSX here */}
);
};
export default GenerateCentralTendencies;
This React script views existing data by sending a GET request to a specified URL with a payload. It handles the response, logging success or failure messages along with the response data.
import React, { useEffect } from 'react';
const ViewExistingData = () => {
const url = "https://example.com/api";
const payload = {
api_key: "your_api_key",
Process_id: 123,
};
useEffect(() => {
const fetchData = async () => {
try {
const response = await fetch(url, {
method: 'GET',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify(payload),
});
if (response.status === 201) {
console.log("Resource retrieved successfully");
const data = await response.json();
console.log(data);
} else {
console.log(`Request failed with status code: ${response.status}`);
console.log(await response.text());
}
} catch (error) {
console.log(`Request failed with an exception: ${error.message}`);
}
};
fetchData();
}, [url, payload]);
return (
{/* Your React component JSX here */}
);
};
export default ViewExistingData;
This Flutter script generates central tendencies by sending a POST request to a specified URL with a payload. It handles the response, printing success or failure messages along with the response data.
import 'dart:convert';
import 'package:http/http.dart' as http;
void main() {
generateCentralTendencies();
}
void generateCentralTendencies() async {
final url = Uri.parse("https://example.com/api");
final payload = {
"api_key": "your_api_key",
"title": "demo-case4",
"Process_id": 122,
"processSequenceId": 11,
"series": 4,
"seriesvalues": {
"list1": [3, 3, 3, 2, 1, 1, 2, 5, 6, 15],
"list2": [11, 2, 2, 4, 2, 2, 5, 6, 8, 9],
"list3": [9, 2, 3, 3, 4, 4, 4, 7, 8, 9],
"list4": [1, 2, 3, 4, 4, 4, 4, 2, 2, 8],
"list5": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
},
};
try {
final response = await http.post(
url,
headers: {'Content-Type': 'application/json'},
body: jsonEncode(payload),
);
if (response.statusCode == 201) {
print("Resource created successfully");
final data = jsonDecode(response.body);
print(data);
} else {
print("Request failed with status code: ${response.statusCode}");
print(response.body);
}
} catch (error) {
print("Request failed with an exception: $error");
}
}
This Flutter script views existing data by sending a GET request to a specified URL with a payload. It handles the response, printing success or failure messages along with the response data.
import 'dart:convert';
import 'package:http/http.dart' as http;
void main() {
viewExistingData();
}
void viewExistingData() async {
final url = Uri.parse("https://example.com/api");
final payload = {
"api_key": "your_api_key",
"Process_id": 123,
};
try {
final response = await http.get(
url,
headers: {'Content-Type': 'application/json'},
body: jsonEncode(payload),
);
if (response.statusCode == 201) {
print("Resource retrieved successfully");
final data = jsonDecode(response.body);
print(data);
} else {
print("Request failed with status code: ${response.statusCode}");
print(response.body);
}
} catch (error) {
print("Request failed with an exception: $error");
}
}
Step 1: Set up the API name, unique ID and the base url(below). It’s a prerequisite to have WP-GET API plugin installed in your wordpress website
Step 2: Establish the API endpoint with the inclusion of the API key, and configure the request body to contain the required POST fields.
Step 3: Test the endpoint to obtain a jQuery response from the API. Ensure that the API is functioning correctly by sending a test request and examining the response.
D’Well Research validates and explores each stage of open innovation using user experience research from the field to support user-centered product design of medium and large companies globally.