dataframe-to-superset 0.1.2

A Python package to upload pandas DataFrames to Superset for easy visualization.

DataFrame to Superset

A Python package to upload pandas DataFrames to Superset. The goal is to visualize your DataFrame inside Superset by providing an easy way to access your data in Superset.

You need a database/datasource in Superset which allows you to upload CSV files. It is recommended to create a separate database/datasource for this purpose and to always keep the name the same when uploading because it overwrites by default. This will help combat clutter created by this package.

Installation

You can install the package using pip:

pip install dataframe-to-superset

Usage

There are three ways to upload a pandas DataFrame to Superset:

1. Creating an object of DataFrameToSuperset

from dataframe_to_superset import DataFrameToSuperset
import pandas as pd

# Create a DataFrameToSuperset object
uploader = DataFrameToSuperset(
    base_url="http://your-superset-instance",
    username="your-username",
    password="your-password",
    provider="db",  # or "ldap"
    database_name="your-database-name",
    schema="public"  # optional, defaults to "public"
)

# Create a pandas DataFrame
df = pd.DataFrame({
    "name": ["Alice", "Bob", "Charlie"],
    "age": [25, 30, 35],
    "join_date": pd.to_datetime(["2021-01-01", "2021-06-15", "2021-09-30"])
})

# Upload the DataFrame
accessable_url = uploader.to_superset(df, name="employees_dataset")
print(accessable_url)

2. Using upload_dataframe_to_superset

from dataframe_to_superset import upload_dataframe_to_superset
import pandas as pd

# Create a pandas DataFrame
df = pd.DataFrame({
    "name": ["Alice", "Bob", "Charlie"],
    "age": [25, 30, 35],
    "join_date": pd.to_datetime(["2021-01-01", "2021-06-15", "2021-09-30"])
})

# Upload the DataFrame
accessable_url = upload_dataframe_to_superset(
    dataframe=df,
    base_url="http://your-superset-instance",
    username="your-username",
    password="your-password",
    provider="db",  # or "ldap"
    database_name="your-database-name",
    schema="public",  # optional, defaults to "public"
    name="employees_dataset"  # optional, defaults to a generated name
)
print(accessable_url)

3. Applying the monkey patch

from dataframe_to_superset import monkey_patch_to_allow_df_to_superset
import pandas as pd

# Apply the monkey patch
monkey_patch_to_allow_df_to_superset(
    base_url="http://your-superset-instance",
    username="your-username",
    password="your-password",
    provider="db",  # or "ldap"
    database_name="your-database-name",
    schema="public",  # optional, defaults to "public"
)

# Create a pandas DataFrame
df = pd.DataFrame({
    "name": ["Alice", "Bob", "Charlie"],
    "age": [25, 30, 35],
    "join_date": pd.to_datetime(["2021-01-01", "2021-06-15", "2021-09-30"])
})

df.name = 'people'

# Upload the DataFrame using the new method
accessable_url = df.to_superset()
print(accessable_url)