def test_dict_list_tuple():
# pandas encoderizer example
X = [
"[text encoding is fun]",
"this is a text encoding {'pizza': 'example'}",
"hopefully it works and [we'll have passed] the test",
]
df = pd.DataFrame({
"text_col":
X * 4,
"categorical_str_col": ["control", "treatment", "control"] * 4,
"categorical_int_col": [0, 1, 2] * 4,
"numeric_col": [5, 22, 69] * 4,
"dict_col": [{
"a": 4
}, {
"b": 1
}, {
"c": 3
}] * 4,
"list_col": [[1, 2], [1, 3], [2]] * 4,
"tuple_col": [(1, 2), (1, 3), (2, )] * 4,
})
encoderizer = encoder.Encoderizer(size="medium")
X_t = encoderizer.fit_transform(df)
assert X_t.shape == (12, 244)
def test_simple():
# simple encoderizer example
X = [
"text encoding is fun",
"this is a text encoding example",
"hopefully it works and we'll have passed the test"
]
encoderizer = encoder.Encoderizer(col_names=["text"])
X_t = encoderizer.fit_transform(X)
assert X_t.shape == (3,31)
def test_dict_list():
# pandas encoderizer example
X = [
"[text encoding is fun]",
"this is a text encoding {'pizza': 'example'}",
"hopefully it works and [we'll have passed] the test"
]
df = pd.DataFrame({
"text": X*4,
"constant_str": ["test","test","test"]*4,
"dicts": [{"a": 4}, None, {"b": 1}]*4,
"lists": [["this", "is", "text"], ["more", "text"], ["text"]]*4
})
encoderizer = encoder.Encoderizer(size="medium")
X_t = encoderizer.fit_transform(df)
assert X_t.shape == (12, 210)
def test_pandas():
# pandas encoderizer example
X = [
"text encoding is fun",
"this is a text encoding example",
"hopefully it works and we'll have passed the test"
]
df = pd.DataFrame({
"text": X*4,
"constant_int": [np.nan,2,2]*4,
"constant_str": ["test","test","test"]*4,
"constant_null": [None,"test",np.nan]*4,
"numbers": [0.123, None, 0.535]*4,
"dicts": [{"a": 4}, None, {"b": 1}]*4
})
encoderizer = encoder.Encoderizer(size="medium")
X_t = encoderizer.fit_transform(df)
assert X_t.shape == (12, 180)