{"id":12107,"date":"2022-01-31T13:28:56","date_gmt":"2022-01-31T12:28:56","guid":{"rendered":"https:\/\/flaven.fr\/?post_type=bf_videos_manager&#038;p=12107"},"modified":"2022-02-01T12:07:06","modified_gmt":"2022-02-01T11:07:06","slug":"part-1-exploratory-data-analysis-or-eda-in-data-science-made-easy-with-sweetviz-pandas-profiling-and-streamlit","status":"publish","type":"bf_videos_manager","link":"https:\/\/flaven.fr\/videos\/part-1-exploratory-data-analysis-or-eda-in-data-science-made-easy-with-sweetviz-pandas-profiling-and-streamlit\/","title":{"rendered":"Part 1 Exploratory Data Analysis or EDA in Data Science made easy with SWEETVIZ, PANDAS PROFILING and Streamlit"},"content":{"rendered":"<p><b>QUICK DESCRIPTION<\/b><br \/>\nA quick presentation in videos on Exploratory Data Analysis or EDA in Data Science made easy with SWEETVIZ, PANDAS PROFILING and Streamlit for the Github repo below.<\/p>\n<p><b>All the files are available on my GitHub account <a href=\"https:\/\/github.com\/bflaven\/BlogArticlesExamples\/tree\/master\/streamlit-sweetviz-pandas-profiling-eda-made-easy\" target=\"_blank\" rel=\"noopener\">https:\/\/github.com\/bflaven\/BlogArticlesExamples\/tree\/master\/streamlit-sweetviz-pandas-profiling-eda-made-easy<\/a><\/b><\/p>\n<p><b>PART_1 (tedious_manual_eda)<\/b><br \/>\nAn example with a very basic data exploration to show how time consuming can be the EDA building process where you need to code and extract relevant information. Nevertheless, the advantage of do-it by yourself will provide you a good chance to fully understand all the operation required for a EDA.<\/p>\n<p><b>PART_4 (streamlit_eda_made_easy_pandas_profiling_4)<\/b><br \/>\nA great and robust library that do the job one for all. An handy &#8220;swiss army knife&#8221; to investigate quickly dataset and generate clean report supported with Streamlit.<\/p>\n<ul>\n<li><b>Streamlit<\/b>: Streamlit turns data scripts into shareable web apps in minutes. All in Python. All for free. No front\u2011end experience required. More on <a href=\"https:\/\/streamlit.io\/\" target=\"_blank\" rel=\"noopener\">https:\/\/streamlit.io\/<\/a><\/li>\n<li><b>SWEETVIZ<\/b>: A dataviz librairie in Python. More on <a href=\"https:\/\/libraries.io\/pypi\/sweetviz\" target=\"_blank\" rel=\"noopener\">https:\/\/libraries.io\/pypi\/sweetviz<\/a><\/li>\n<li><b>Pandas Profiling<\/b>: A dataviz librairie in Python. More on <a href=\"https:\/\/pypi.org\/project\/pandas-profiling\/\" target=\"_blank\" rel=\"noopener\">https:\/\/pypi.org\/project\/pandas-profiling\/<\/a><\/li>\n<li><b>Sweetviz: Automate Exploratory Data Analysis (EDA)<\/b> A great article on Sweetviz. More on <a href=\"https:\/\/coderzcolumn.com\/tutorials\/data-science\/sweetviz-automate-exploratory-data-analysis-eda\" target=\"_blank\" rel=\"noopener\">https:\/\/coderzcolumn.com\/tutorials\/data-science\/sweetviz-automate-exploratory-data-analysis-eda<\/a><\/li>\n<li><b>Toy datasets<\/b>: Toy Datasets from Scikit. More on <a href=\"https:\/\/scikit-learn.org\/stable\/datasets\/toy_dataset.html\" target=\"_blank\" rel=\"noopener\">https:\/\/scikit-learn.org\/stable\/datasets\/toy_dataset.html<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>QUICK DESCRIPTION A quick presentation in videos on Exploratory Data Analysis or EDA in Data Science made easy with SWEETVIZ, PANDAS PROFILING and Streamlit for&hellip; <\/p>\n<p class=\"text-center\"><a href=\"https:\/\/flaven.fr\/videos\/part-1-exploratory-data-analysis-or-eda-in-data-science-made-easy-with-sweetviz-pandas-profiling-and-streamlit\/\" class=\"more-link\">Continue reading &rarr; <span class=\"screen-reader-text\">Part 1 Exploratory Data Analysis or EDA in Data Science made easy with SWEETVIZ, PANDAS PROFILING and Streamlit<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":11806,"comment_status":"open","ping_status":"closed","template":"","bf_videos_manager_tag":[2707,2866,2870,2864,2871,2867,2869,2868,2865],"bf_videos_manager_cat":[2681,2678,2721,2679,2680],"class_list":["post-12107","bf_videos_manager","type-bf_videos_manager","status-publish","has-post-thumbnail","hentry","bf_videos_manager_tag-agile","bf_videos_manager_tag-application","bf_videos_manager_tag-automate","bf_videos_manager_tag-dashboard","bf_videos_manager_tag-data-science","bf_videos_manager_tag-eda","bf_videos_manager_tag-pandas-profiling","bf_videos_manager_tag-sweetviz","bf_videos_manager_tag-webtool","bf_videos_manager_cat-development","bf_videos_manager_cat-python","bf_videos_manager_cat-training","bf_videos_manager_cat-tutorials","bf_videos_manager_cat-videos"],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/bf_videos_manager\/12107","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/bf_videos_manager"}],"about":[{"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/types\/bf_videos_manager"}],"author":[{"embeddable":true,"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/comments?post=12107"}],"version-history":[{"count":6,"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/bf_videos_manager\/12107\/revisions"}],"predecessor-version":[{"id":12122,"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/bf_videos_manager\/12107\/revisions\/12122"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/media\/11806"}],"wp:attachment":[{"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/media?parent=12107"}],"wp:term":[{"taxonomy":"bf_videos_manager_tag","embeddable":true,"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/bf_videos_manager_tag?post=12107"},{"taxonomy":"bf_videos_manager_cat","embeddable":true,"href":"https:\/\/flaven.fr\/happy-api\/wp\/v2\/bf_videos_manager_cat?post=12107"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}