pycatdap/__init__.py,sha256=h5l03sfvTIxBL4YniyH54JrZazjoCTn8_PY9BGNJbeQ,1944
pycatdap/_aic.py,sha256=9IIBAT52C6TrMDpzJ1cxaKnmkQ18t6tKmBX6DkzC8EE,5646
pycatdap/_aic_regression.py,sha256=Dm0gc2W4PCyLLHkhSZbQLD5JaOWm316BxzJUCUdQsuo,7585
pycatdap/_association.py,sha256=XTlQuWxybRUDRbiwtXP-sV51MN3tkSK_AznYAmpJgYQ,6755
pycatdap/_contingency.py,sha256=srgFgtY-pX_W25JGLtRpMAJkNRIKd3aO0vRBwJ0hgzw,4008
pycatdap/_io.py,sha256=j8nOcqDjdDm_MEG5XkMKV2MDdMzY3anKKqMFfcg1IXg,1695
pycatdap/_pooling.py,sha256=KKEKsppBLfQehbyuHFtWXKW8esWJmVw_mYjO9bF7kWE,10936
pycatdap/_quality.py,sha256=cwNVyTTAwNqXFYSrW5_vaP9W9_UwWM3TB5ucx3NwaNw,6537
pycatdap/_subset_search.py,sha256=kniakSBMTfX0OoMtahaFmu4NqpYuNzAXIIDA0yxCdsQ,3946
pycatdap/_target_pair.py,sha256=mIj80OnCwiscQ3QQKef5uAY4Z0B8_3l9y4mGCtp0cmo,30431
pycatdap/_version.py,sha256=A-lpWVGGoQBH6e2nfNV1N5GInFp03GJS_egfGMxtfBU,520
pycatdap/catdap1.py,sha256=3U3lxZX1uAUnfPxkIHwgJ-j-R5aI_fqZgh_QMtFUlGY,6109
pycatdap/catdap2.py,sha256=jUC1Fwbe9wrowsj1Zgk9-dbs-M_7BNk6dgY78a9CnP0,8587
pycatdap/datasets.py,sha256=wfEY5fGYq7_ovffP7Q8ZmZOPs4CNegRaca0F9M3zz_A,4606
pycatdap/eda.py,sha256=tkrxjLnBvjYFbi_eJHmOeBdYzOvxQFodcy_dwU-nErI,8265
pycatdap/plotting.py,sha256=UHTU-KP8e64NpwuoCITAQv51gQHnooQpF8wvDpqRDBM,875
pycatdap/profile.py,sha256=jKoauFKN_vSfWs22eCx57Vyz-vO_31rxBSHPzDskSpY,19743
pycatdap/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pycatdap/quality_report.py,sha256=IIbAifIGWR-KoRkxmhiTM7bHU569k1Ymf9-EDKKaJt4,9606
pycatdap/target_analysis.py,sha256=faYLzFyXyiNTi5FcseeeFaOnFZtP9HB5kL8VIqdrqXY,11619
pycatdap/data/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
pycatdap/data/health_data.csv,sha256=dva2YzK0ywCs_bjfSihAZG5Atnw52Ncy8WO0xRTSsB0,1351
pycatdap/data/hello_goodbye.csv.gz,sha256=9-9--9fy_HV-ldP6Lf7hwy-5soNp8lxsRjjTrz2e5Nc,32001
pycatdap/data/iris.csv,sha256=PYezN3WDdFXu5lYwfyQDfb2C1xki0jMLQieNFzvqAXk,3858
pycatdap/data/titanic.csv,sha256=aK9uCfSKIiFWuKZ3oN2iuTwD6RCFGN_ijZtPqwA3mDg,42177
pycatdap/measures/__init__.py,sha256=3l_XT0rM6JV6tbo8i-84hNnsgaPfF4uC7JUau71H1H0,1377
pycatdap/measures/_aic.py,sha256=4bWpBD9VGtPjtjT7PDgvCHrzdwxLWX6V1eu-mH7DYp8,1693
pycatdap/measures/_cramers_v.py,sha256=3JmxXy4F4ZhBp793h5zTj3HdTcv81mX-pcAReqy8WXI,2238
pycatdap/measures/_mutual_info.py,sha256=o3ZmneJ6v2lWbigWThYiHo1iUOqkdSWleuSpFF0aehg,2081
pycatdap/measures/_registry.py,sha256=elyA5lXz1tWqz8I_buE8-Fo4CZs8ZAOXaLuD7NdYBPQ,2151
pycatdap/plot/__init__.py,sha256=HN8ilODS-Xrsbm0A8VZRWP6qsSsngGn2G43dfd2C8-E,13714
pycatdap/plot/matplotlib.py,sha256=v1Rhdox7-JtqbIz6cFkXkp0l99pR2AamHs4VIfZjkmY,27061
pycatdap/plot/plotly.py,sha256=4d8emxOEantg6s_gw5NebwXs_siJ2hn1qitn29Mr9go,26439
pycatdap/suite/__init__.py,sha256=XWF-otulyqTJ82YkLFVRb7wkdL6-OjoaDroKG2sPs4M,1201
pycatdap/suite/_base.py,sha256=yixWPOXa6q6iwGuyZhJgNbkwV-GU_NjYyNI3cDF0VI4,9196
pycatdap/suite/_checks.py,sha256=dl4v4zcNmNPK5uFRT8WNqsaCjzPphO1-ttDURtUjjQI,7846
pycatdap/suite/_suites.py,sha256=bViNhQQCIek9Ha6pt9YQed9Vidqwb86356t2sc_-m6g,2685
pycatdap/templates/__init__.py,sha256=OplpczSRZIm1sNOTdeIUGBTQypjjFGuux0brbNtKc-A,280
pycatdap/templates/profile.html.j2,sha256=nDc8RNmXkJKZpUIyi20d-rmKnlhEJvogdp31yhDMZhs,4532
pycatdap/templates/quality_report.html.j2,sha256=TIY_M2OWWQeBU3ni0PXsXXVp3jzcYrSEpyEEk0F-xeg,2368
pycatdap/templates/suite_result.html.j2,sha256=0hC6ZTKP-R9_L3ajj4NTr8lYtNgaHB9NN5G2g6CUl5A,2635
pycatdap/templates/target_analysis.html.j2,sha256=Tu7xC9IEQCBM0JI50JJS1nKjIMujIYaXgdL9aWB_Xm8,3430
pycatdap-0.6.0.dist-info/METADATA,sha256=cxqA0I4mcggqBFk2ZMTGqSunnhcXki1CMpMy5SRSnA4,7685
pycatdap-0.6.0.dist-info/WHEEL,sha256=QccIxa26bgl1E6uMy58deGWi-0aeIkkangHcxk2kWfw,87
pycatdap-0.6.0.dist-info/licenses/LICENSE,sha256=SOGXSV-d2beNHuiwhkL2nfLl-_sSTY3d3JEqDmhamcE,1064
pycatdap-0.6.0.dist-info/RECORD,,
