Data Mining - Pokemon Analysis - Computer Science bibliographies - in Harvard style

In-text: (Barradas, 2016)

Your Bibliography: Barradas, A., 2016. Pokemon with stats | Kaggle. [online] Kaggle.com. Available at: <https://www.kaggle.com/abcsds/pokemon> [Accessed 7 March 2018].

In-text: (Dutt, 2017)

Your Bibliography: Dutt, A., 2017. pokemon data analysis | Kaggle. [online] Kaggle.com. Available at: <https://www.kaggle.com/abhinav97dutt/pokemon-data-analysis> [Accessed 7 March 2018].

In-text: (Huq, 2017)

Your Bibliography: Huq, R., 2017. Exploring the Pokemon dataset with pandas and seaborn. [online] In Machines We Trust. Available at: <http://inmachineswetrust.com/posts/exploring-pokemon-dataset/> [Accessed 7 March 2018].

In-text: (Kim, 2017)

Your Bibliography: Kim, R., 2017. Pokemon Generation Gap? (Python Data Analysis) — Part 1: cleaning, EDA. [online] Towards Data Science. Available at: <https://towardsdatascience.com/pokemon-generation-gap-python-data-analysis-part-1-cleaning-eda-265ff3cb5dff> [Accessed 7 March 2018].

In-text: (Maës, 2016)

Your Bibliography: Maës, J., 2016. Adapting Pokemon stats to data analysis methods | Kaggle. [online] Kaggle.com. Available at: <https://www.kaggle.com/juneako/adapting-pokemon-stats-to-data-analysis-methods> [Accessed 7 March 2018].

In-text: (Martins, 2016)

Your Bibliography: Martins, M., 2016. Pokemon Data Analysis. [online] Rstudio-pubs-static.s3.amazonaws.com. Available at: <https://rstudio-pubs-static.s3.amazonaws.com/204677_b79ebe5102114597a3400c5f8f67e8f1.html#/> [Accessed 7 March 2018].

In-text: (Munroe, 2017)

Your Bibliography: Munroe, L., 2017. veekun/pokedex. [online] GitHub. Available at: <https://github.com/veekun/pokedex> [Accessed 7 March 2018].