Skip to content

Fix Titanic dataset loading in test_utils.py #1959

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
hertschuh merged 8 commits into from
Nov 25, 2025
Merged

Fix Titanic dataset loading in test_utils.py #1959

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
a74f524
Fix Titanic dataset loading in test_utils.py
pctablet505 Nov 19, 2025
311ae9e
Address code review feedback for test_utils.py
pctablet505 Nov 19, 2025
b8a7884
Fix SSL certificate issues in structured data tests
pctablet505 Nov 20, 2025
f9cdc35
Standardize missing values in Titanic datasets
pctablet505 Nov 20, 2025
1e444df
Update test_utils.py
pctablet505 Nov 20, 2025
d7056d9
Update test_utils.py
pctablet505 Nov 20, 2025
2c77eeb
Update test_utils.py
pctablet505 Nov 20, 2025
28a8e70
Update test_utils.py
pctablet505 Nov 20, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
13 changes: 7 additions & 6 deletions autokeras/test_utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -45,14 +45,15 @@
"embark_town": "categorical",
"alone": "categorical",
}
TRAIN_DATA_URL = "https://storage.googleapis.com/tf-datasets/titanic/train.csv"
TEST_DATA_URL = "https://storage.googleapis.com/tf-datasets/titanic/eval.csv"

TRAIN_CSV_PATH = keras.utils.get_file(
fname=os.path.basename(TRAIN_DATA_URL), origin=TRAIN_DATA_URL
ROOT_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
# Use pre-split CSVs stored under benchmark/datasets to avoid downloads and
# processing at import time.
TRAIN_CSV_PATH = os.path.join(
ROOT_DIR, "benchmark", "datasets", "titanic_train.csv"
)
TEST_CSV_PATH = keras.utils.get_file(
fname=os.path.basename(TEST_DATA_URL), origin=TEST_DATA_URL
TEST_CSV_PATH = os.path.join(
ROOT_DIR, "benchmark", "datasets", "titanic_test.csv"
)


Expand Down
263 changes: 263 additions & 0 deletions benchmark/datasets/titanic_test.csv
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,263 @@
sex,age,n_siblings_spouses,parch,fare,class,deck,embark_town,alone,survived
female,15,0,0,7.225,3,?,C,True,1
female,1,0,2,15.7417,3,?,C,False,1
male,20,1,1,15.7417,3,?,C,False,1
female,19,1,1,15.7417,3,?,C,False,1
male,33,0,0,8.05,3,?,S,True,0
male,,0,0,7.8958,3,?,S,True,0
male,,0,0,7.2292,3,?,C,True,0
female,,0,0,7.75,3,?,Q,True,0
male,,0,0,7.8958,3,?,S,True,0
male,12,1,0,11.2417,3,?,C,False,1
female,14,1,0,11.2417,3,?,C,False,1
female,29,0,0,7.925,3,?,S,True,0
male,28,0,0,8.05,3,?,S,True,0
female,18,0,0,7.775,3,?,S,True,1
female,26,0,0,7.8542,3,?,S,True,1
male,21,0,0,7.8542,3,?,S,True,0
male,41,0,0,7.125,3,?,S,True,0
male,39,0,0,7.925,3,?,S,True,1
male,21,0,0,7.8,3,?,S,True,0
male,28.5,0,0,7.2292,3,?,C,True,0
female,22,0,0,7.75,3,?,S,True,1
male,61,0,0,6.2375,3,?,S,True,0
male,,1,0,15.5,3,?,Q,False,0
male,,0,0,7.8292,3,?,Q,True,0
female,,1,0,15.5,3,?,Q,False,1
male,,0,0,7.7333,3,?,Q,True,0
male,,0,0,7.75,3,?,Q,True,0
male,,0,0,7.75,3,?,Q,True,0
male,23,0,0,9.225,3,?,S,True,0
female,,0,0,7.75,3,?,Q,True,0
female,,0,0,7.75,3,?,Q,True,1
female,,0,0,7.8792,3,?,Q,True,1
female,22,0,0,7.775,3,?,S,True,1
male,,0,0,7.75,3,?,Q,True,1
female,,0,0,7.8292,3,?,Q,True,1
male,9,0,1,3.1708,3,?,S,False,1
male,28,0,0,22.525,3,?,S,True,0
male,42,0,1,8.4042,3,?,S,False,0
male,,0,0,7.3125,3,?,S,True,0
female,31,0,0,7.8542,3,?,S,True,0
male,28,0,0,7.8542,3,?,S,True,0
male,32,0,0,7.775,3,?,S,True,1
male,20,0,0,9.225,3,?,S,True,0
female,23,0,0,8.6625,3,?,S,True,0
female,20,0,0,8.6625,3,?,S,True,0
male,20,0,0,8.6625,3,?,S,True,0
male,16,0,0,9.2167,3,?,S,True,0
female,31,0,0,8.6833,3,?,S,True,1
female,,0,0,7.6292,3,?,Q,True,0
male,2,3,1,21.075,3,?,S,False,0
male,6,3,1,21.075,3,?,S,False,0
female,3,3,1,21.075,3,?,S,False,0
female,8,3,1,21.075,3,?,S,False,0
female,29,0,4,21.075,3,?,S,False,0
male,1,4,1,39.6875,3,?,S,False,0
male,7,4,1,39.6875,3,?,S,False,0
male,2,4,1,39.6875,3,?,S,False,0
male,16,4,1,39.6875,3,?,S,False,0
male,14,4,1,39.6875,3,?,S,False,0
female,41,0,5,39.6875,3,?,S,False,0
male,21,0,0,8.6625,3,?,S,True,0
male,19,0,0,14.5,3,?,S,True,0
male,,0,0,8.7125,3,?,C,True,0
male,32,0,0,7.8958,3,?,S,True,0
male,0.75,1,1,13.775,3,?,S,False,0
female,3,1,1,13.775,3,?,S,False,0
female,26,0,2,13.775,3,?,S,False,0
male,,0,0,7,3,?,S,True,0
male,,0,0,7.775,3,?,S,True,0
male,,0,0,8.05,3,?,S,True,0
male,21,0,0,7.925,3,?,S,True,0
male,25,0,0,7.925,3,?,S,True,0
male,22,0,0,7.25,3,?,S,True,0
male,25,1,0,7.775,3,?,S,False,1
male,,1,1,22.3583,3,?,C,False,1
female,,1,1,22.3583,3,F E69,C,False,1
female,,0,2,22.3583,3,?,C,False,1
female,,0,0,8.1375,3,?,Q,True,0
male,24,0,0,8.05,3,?,S,True,0
female,28,0,0,7.8958,3,?,S,True,0
male,19,0,0,7.8958,3,?,S,True,0
male,,0,0,7.8958,3,?,S,True,0
male,25,1,0,7.775,3,?,S,False,0
female,18,0,0,7.775,3,?,S,True,0
male,32,0,0,8.05,3,E10,S,True,1
male,,0,0,7.8958,3,?,S,True,0
male,17,0,0,8.6625,3,?,S,True,0
male,24,0,0,8.6625,3,?,S,True,0
male,,0,0,7.8958,3,?,S,True,0
female,,0,0,8.1125,3,?,S,True,0
male,,0,0,7.2292,3,?,C,True,0
male,,0,0,7.25,3,?,S,True,0
male,38,0,0,7.8958,3,?,S,True,0
male,21,0,0,8.05,3,?,S,True,0
male,10,4,1,29.125,3,?,Q,False,0
male,4,4,1,29.125,3,?,Q,False,0
male,7,4,1,29.125,3,?,Q,False,0
male,2,4,1,29.125,3,?,Q,False,0
male,8,4,1,29.125,3,?,Q,False,0
female,39,0,5,29.125,3,?,Q,False,0
female,22,0,0,39.6875,3,?,S,True,0
male,35,0,0,7.125,3,?,S,True,0
female,,0,0,7.7208,3,?,Q,True,1
male,,0,0,14.5,3,?,S,True,0
female,,0,0,14.5,3,?,S,True,0
male,50,1,0,14.5,3,?,S,False,0
female,47,1,0,14.5,3,?,S,False,0
male,,0,0,8.05,3,?,S,True,0
male,,0,0,7.775,3,?,S,True,0
female,2,1,1,20.2125,3,?,S,False,0
male,18,1,1,20.2125,3,?,S,False,0
female,41,0,2,20.2125,3,?,S,False,0
female,,0,0,8.05,3,?,S,True,1
male,50,0,0,8.05,3,?,S,True,0
male,16,0,0,8.05,3,?,S,True,0
male,,0,0,7.75,3,?,Q,True,1
male,,0,0,24.15,3,?,Q,True,0
male,,0,0,7.2292,3,?,C,True,0
male,25,0,0,7.225,3,?,C,True,0
male,,0,0,7.225,3,?,C,True,0
male,,0,0,7.7292,3,?,Q,True,0
male,,0,0,7.575,3,?,S,True,0
male,38.5,0,0,7.25,3,?,S,True,0
male,,8,2,69.55,3,?,S,False,0
male,14.5,8,2,69.55,3,?,S,False,0
female,,8,2,69.55,3,?,S,False,0
female,,8,2,69.55,3,?,S,False,0
female,,8,2,69.55,3,?,S,False,0
female,,8,2,69.55,3,?,S,False,0
male,,8,2,69.55,3,?,S,False,0
male,,8,2,69.55,3,?,S,False,0
male,,8,2,69.55,3,?,S,False,0
male,,1,9,69.55,3,?,S,False,0
female,,1,9,69.55,3,?,S,False,0
male,24,0,0,9.325,3,?,S,True,0
female,21,0,0,7.65,3,?,S,True,1
male,39,0,0,7.925,3,?,S,True,0
male,,2,0,21.6792,3,?,C,False,0
male,,2,0,21.6792,3,?,C,False,0
male,,2,0,21.6792,3,?,C,False,0
female,1,1,1,16.7,3,G6,S,False,1
female,24,0,2,16.7,3,G6,S,False,1
female,4,1,1,16.7,3,G6,S,False,1
male,25,0,0,9.5,3,?,S,True,1
male,20,0,0,8.05,3,?,S,True,0
male,24.5,0,0,8.05,3,?,S,True,0
male,,0,0,7.725,3,?,Q,True,0
male,,0,0,7.8958,3,?,S,True,0
male,,0,0,7.75,3,?,Q,True,0
male,29,0,0,9.5,3,?,S,True,1
male,,0,0,15.1,3,?,S,True,0
female,,0,0,7.7792,3,?,Q,True,1
male,,0,0,8.05,3,?,S,True,0
male,,0,0,8.05,3,?,S,True,0
male,22,0,0,7.2292,3,?,C,True,0
male,,0,0,8.05,3,?,S,True,0
male,40,0,0,7.8958,3,?,S,True,0
male,21,0,0,7.925,3,?,S,True,0
female,18,0,0,7.4958,3,?,S,True,1
male,4,3,2,27.9,3,?,S,False,0
male,10,3,2,27.9,3,?,S,False,0
female,9,3,2,27.9,3,?,S,False,0
female,2,3,2,27.9,3,?,S,False,0
male,40,1,4,27.9,3,?,S,False,0
female,45,1,4,27.9,3,?,S,False,0
male,,0,0,7.8958,3,?,S,True,0
male,,0,0,8.05,3,?,S,True,0
male,,0,0,8.6625,3,?,S,True,0
male,,0,0,7.75,3,?,Q,True,0
female,,0,0,7.7333,3,?,Q,True,1
male,19,0,0,7.65,3,F G73,S,True,0
male,30,0,0,8.05,3,?,S,True,0
male,,0,0,8.05,3,?,S,True,0
male,32,0,0,8.05,3,?,S,True,0
male,,0,0,7.8958,3,?,S,True,0
male,33,0,0,8.6625,3,?,C,True,0
female,23,0,0,7.55,3,?,S,True,1
male,21,0,0,8.05,3,?,S,True,0
male,60.5,0,0,?,3,?,S,True,0
male,19,0,0,7.8958,3,?,S,True,0
female,22,0,0,9.8375,3,?,S,True,0
male,31,0,0,7.925,3,?,S,True,1
male,27,0,0,8.6625,3,?,S,True,0
female,2,0,1,10.4625,3,G6,S,False,0
female,29,1,1,10.4625,3,G6,S,False,0
male,16,0,0,8.05,3,?,S,True,1
male,44,0,0,7.925,3,?,S,True,1
male,25,0,0,7.05,3,?,S,True,0
male,74,0,0,7.775,3,?,S,True,0
male,14,0,0,9.225,3,?,S,True,1
male,24,0,0,7.7958,3,?,S,True,0
male,25,0,0,7.7958,3,?,S,True,1
male,34,0,0,8.05,3,?,S,True,0
male,0.4167,0,1,8.5167,3,?,C,False,1
male,,1,0,6.4375,3,?,C,False,0
male,,0,0,6.4375,3,?,C,True,0
male,,0,0,7.225,3,?,C,True,0
female,16,1,1,8.5167,3,?,C,False,1
male,,0,0,8.05,3,?,S,True,0
male,,1,0,16.1,3,?,S,False,0
female,,1,0,16.1,3,?,S,False,1
male,32,0,0,7.925,3,?,S,True,0
male,,0,0,7.75,3,F38,Q,True,0
male,,0,0,7.8958,3,?,S,True,0
male,30.5,0,0,8.05,3,?,S,True,0
male,44,0,0,8.05,3,?,S,True,0
male,,0,0,7.2292,3,?,C,True,0
male,25,0,0,0,3,?,S,True,1
male,,0,0,7.2292,3,?,C,True,0
male,7,1,1,15.2458,3,?,C,False,1
female,9,1,1,15.2458,3,?,C,False,1
female,29,0,2,15.2458,3,?,C,False,1
male,36,0,0,7.8958,3,?,S,True,0
female,18,0,0,9.8417,3,?,S,True,1
female,63,0,0,9.5875,3,?,S,True,1
male,,1,1,14.5,3,?,S,False,0
male,11.5,1,1,14.5,3,?,S,False,0
male,40.5,0,2,14.5,3,?,S,False,0
female,10,0,2,24.15,3,?,S,False,0
male,36,1,1,24.15,3,?,S,False,0
female,30,1,1,24.15,3,?,S,False,0
male,,0,0,9.5,3,?,S,True,0
male,33,0,0,9.5,3,?,S,True,0
male,28,0,0,9.5,3,?,S,True,0
male,28,0,0,9.5,3,?,S,True,0
male,47,0,0,9,3,?,S,True,0
female,18,2,0,18,3,?,S,False,0
male,31,3,0,18,3,?,S,False,0
male,16,2,0,18,3,?,S,False,0
female,31,1,0,18,3,?,S,False,0
male,22,0,0,7.225,3,?,C,True,1
male,20,0,0,7.8542,3,?,S,True,0
female,14,0,0,7.8542,3,?,S,True,0
male,22,0,0,7.8958,3,?,S,True,0
male,22,0,0,9,3,?,S,True,0
male,,0,0,8.05,3,?,S,True,0
male,,0,0,7.55,3,?,S,True,0
male,,0,0,8.05,3,?,S,True,0
male,32.5,0,0,9.5,3,?,S,True,0
female,38,0,0,7.2292,3,?,C,True,1
male,51,0,0,7.75,3,?,S,True,0
male,18,1,0,6.4958,3,?,S,False,0
male,21,1,0,6.4958,3,?,S,False,0
female,47,1,0,7,3,?,S,False,1
male,,0,0,8.7125,3,?,S,True,0
male,,0,0,7.55,3,?,S,True,0
male,,0,0,8.05,3,?,S,True,0
male,28.5,0,0,16.1,3,?,S,True,0
male,21,0,0,7.25,3,?,S,True,0
male,27,0,0,8.6625,3,?,S,True,0
male,,0,0,7.25,3,?,S,True,0
male,36,0,0,9.5,3,?,S,True,0
male,27,1,0,14.4542,3,?,C,False,0
female,15,1,0,14.4542,3,?,C,False,1
male,45.5,0,0,7.225,3,?,C,True,0
male,,0,0,7.225,3,?,C,True,0
male,,0,0,14.4583,3,?,C,True,0
female,14.5,1,0,14.4542,3,?,C,False,0
female,,1,0,14.4542,3,?,C,False,0
male,26.5,0,0,7.225,3,?,C,True,0
male,27,0,0,7.225,3,?,C,True,0
male,29,0,0,7.875,3,?,S,True,0
Loading
Loading