Created
April 19, 2023 06:44
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# Dependencies to install: Pandas for dataframes, pyarrow to support the feather file format. | |
# pip install pandas | |
# pip install pyarrow | |
# Load a downloaded dataset from file: | |
train_df = pd.read_feather("train.feather") | |
train_df.head() | |
# The dataset contains 220 features per query-document (columns starting with 'feature_*') | |
# Here is one of many ways to select all columns starting with 'feature_' | |
train_df.filter(regex="^feature_", axis=1).head() | |
# The field query_id signals which query-document vectors belong to the same search query. | |
train_df["query_id"].head() | |
# The relevance column contains the human expert judgments how relevant each document was for the current query (scale 0 - 4) | |
train_df["relevance"].head() |
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