Functions

Summary

function class parent truncated documentation
_setup_hook   if this function is added to the module, the help automation and unit tests call it first before anything goes on …
check   Checks the library is working. It raises an exception. If you want to disable the logs:
dataframe_hash_columns   Hashes a set of columns in a dataframe. Keeps the same type. Skips missing values.
dataframe_shuffle   Shuffles a dataframe.
dataframe_unfold   One column may contain concatenated values. This function splits these values and multiplies the rows for each split …
dummy_streaming_dataframe   Returns a dummy streaming dataframe mostly for unit test purposes.
enumerate_json_items   Enumerates items from a JSON file or string.
flatten_dictionary   Flattens a dictionary with nested structure to a dictionary with no hierarchy.
hash_float   Hashes a float into a float.
hash_int   Hashes an integer into an integer.
hash_str   Hashes a string.
numpy_types   Returns the list of numpy available types.
pandas_fillna   Replaces the :epkg:`nan` values for something not :epkg:`nan`. Mostly used by pandas_groupby_nan().
pandas_groupby_nan   Does a groupby including keeping missing values (:epkg:`nan`).
read_zip   Reads a dataframe from a zip file. It can be saved by read_zip().
sklearn_train_test_split   Randomly splits a dataframe into smaller pieces. The function returns streams of file names. The function relies …
sklearn_train_test_split_streaming   Randomly splits a dataframe into smaller pieces. The function returns streams of file names. The function relies …
to_zip   Saves a Dataframe into a zip file. It can be read by to_zip().
train_test_apart_stratify   This split is for a specific case where data is linked in one way. Let’s assume we have two ids as we have for online …
train_test_connex_split   This split is for a specific case where data is linked in many ways. Let’s assume we have three ids as we have for …
train_test_split_weights   Splits a database in train/test given, every row can have a different weight.