Convert pandas dataframe to datasetDict-CodePudding

I cannot find anywhere how to convert a pandas dataframe to type datasets.dataset_dict.DatasetDict, for optimal use in a BERT workflow with a huggingface model. Take these simple dataframes, for example.

train_df = pd.DataFrame({
     "label" : [1, 2, 3],
     "text" : ["apple", "pear", "strawberry"]
})

test_df = pd.DataFrame({
     "label" : [2, 2, 1],
     "text" : ["banana", "pear", "apple"]
})

What is the most efficient way to convert these to the type above?

CodePudding user response：

One possibility is to first create two Datasets and then join them:

import datasets
import pandas as pd


train_df = pd.DataFrame({
     "label" : [1, 2, 3],
     "text" : ["apple", "pear", "strawberry"]
})

test_df = pd.DataFrame({
     "label" : [2, 2, 1],
     "text" : ["banana", "pear", "apple"]
})

train_dataset = Dataset.from_dict(train_df)
test_dataset = Dataset.from_dict(test_df)
my_dataset_dict = datasets.DatasetDict({"train":train_dataset,"test":test_dataset})

The result is:

DatasetDict({
    train: Dataset({
        features: ['label', 'text'],
        num_rows: 3
    })
    test: Dataset({
        features: ['label', 'text'],
        num_rows: 3
    })
})