WOLLER, Fabian, AREND, Lis, FUCHSBERGER, Christian, LIST, Markus und BLUMENTHAL, David B, 2025. NApy: efficient statistics in Python for large-scale heterogeneous data with enhanced support for missing data. Giga Science. 1 Januar 2025. Vol. 14, , p. 1-12. DOI 10.1093/gigascience/giaf140.
Elsevier - Harvard (with titles)Woller, F., Arend, L., Fuchsberger, C., List, M., Blumenthal, D.B., 2025. NApy: efficient statistics in Python for large-scale heterogeneous data with enhanced support for missing data. Giga Science 14, 1-12. https://doi.org/10.1093/gigascience/giaf140
American Psychological Association 7th editionWoller, F., Arend, L., Fuchsberger, C., List, M., & Blumenthal, D. B. (2025). NApy: efficient statistics in Python for large-scale heterogeneous data with enhanced support for missing data. Giga Science, 14, 1-12. https://doi.org/10.1093/gigascience/giaf140
Springer - Basic (author-date)Woller F, Arend L, Fuchsberger C, List M, Blumenthal DB (2025) NApy: efficient statistics in Python for large-scale heterogeneous data with enhanced support for missing data.. Giga Science 14:1-12. https://doi.org/10.1093/gigascience/giaf140
Juristische Zitierweise (Stüber) (Deutsch)Woller, Fabian/ Arend, Lis/ Fuchsberger, Christian/ List, Markus/ Blumenthal, David B, NApy: efficient statistics in Python for large-scale heterogeneous data with enhanced support for missing data., Giga Science 2025, 1-12.