Skip to main content

Uploading your first Dataset

In this example we will examine how upload your first dataset into the platform.

Step 1: Connecting into the platform​

As a first step you will need to connect into the platform using your credentials.

from typing import Final
import evoml_client as ec
import pandas as pd

# Pease replace with your deploy-platform URL
API_URL: Final[str] = "https://evoml.ai"

# Please replace with your username
USERNAME: Final[str] = ""
# Please replace with your password
PASSWORD: Final[str] = ""

# Connect to the platform
ec.init(base_url=API_URL, username=USERNAME, password=PASSWORD)

Step 2: Create and Load your dataset​

Evoml Client library offers a variety of ways on how to create a new Dataset. For example:

  1. By reading from a file using ec.Dataset.from_file() method
  2. By loading a numpy array using ec.Dataset.from_numpy() method
  3. By loading a pandas dataframe using ec.Dataset.from_pandas() method
  4. By ingesting a file from a URL using ec.Dataset.from_url() method

*Supported files include: csv, parquet, avro, feather and hdf5

Now Let's create a small pandas dataframe!

import pandas as pd
import numpy as np

# Create random data for 100 rows and 10 columns
data = np.random.rand(100, 10)

# Define column names
columns = [f"Column_{i+1}" for i in range(10)]

# Create the DataFrame
df = pd.DataFrame(data, columns=columns)

We can use the ec.Dataframe.from_pandas to upload the dataframe into the platform.

dataset = ec.Dataset.from_pandas(df, name="Random Data")
dataset.put()

print(f"Dataset ID: {dataset.dataset_id}")

The dataset is now successfully updated into the platform. You should be able to view the dataset be navigating to the EvoML Platform through your browser.