{"id":702,"date":"2024-04-09T22:13:33","date_gmt":"2024-04-10T02:13:33","guid":{"rendered":"https:\/\/learnwithneha.site\/?p=702"},"modified":"2024-04-10T10:24:21","modified_gmt":"2024-04-10T14:24:21","slug":"elementor-702","status":"publish","type":"post","link":"https:\/\/learnwithneha.site\/?p=702","title":{"rendered":"Data Cleaning Project"},"content":{"rendered":"\t\t
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Data Cleaning Using Panda<\/strong><\/p>

Data cleaning is an essential step in the data analysis process, ensuring that your data is accurate, consistent, and reliable for analysis. Pandas, a popular Python library for data manipulation and analysis, provides powerful tools for data cleaning. Here’s an introduction to data cleaning in Pandas:<\/p>

Import Pandas<\/strong>: Before you start cleaning your data, you need to import the Pandas library. You can do this using the following import statement.<\/p>

Pandas provides various functions to load data from different file formats such as CSV, Excel, SQL databases, etc.<\/p>

For example:<\/p>

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Removing Duplicates<\/strong>: Duplicates in the dataset can skew analysis results. Pandas provides the drop_duplicates()<\/code> method to remove duplicate rows. For example:<\/p>

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Removing unnecessary columns like “not useful”<\/strong><\/p>

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Cleaning up the “last name” column<\/strong>: removing forward slashes, dots etc.<\/p>

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Standardizing phone numbers<\/strong> by removing various formats and NaNs<\/p>

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Handling Address<\/strong> data by splitting it into separate columns for better readability<\/p>

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Standardizing values in the “paying customer” and “Do Not Contact ” column to “Y” and “N”<\/p>

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Remove All NAN<\/strong> and fill it with blank<\/p>

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Remove rows<\/strong> who don’t want to be contacted.<\/p>

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Also Remove the Rows Where we don’t have any phone number<\/strong><\/p>

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Reset Index<\/strong><\/p>

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Note<\/strong> :– “In the end, our data cleaning project has made a big difference. We turned messy data into clear, useful information. By paying attention to details and being careful, we’ve made sure our data is reliable. As we finish up, remember: keeping data clean isn’t just important\u2014it’s the key to understanding and making good decisions.<\/strong>“<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Data Cleaning Using Panda Data cleaning is an essential step in the data analysis process, ensuring that your data is accurate, consistent, and reliable for analysis. Pandas, a popular Python library for data manipulation and analysis, provides powerful tools for data cleaning. Here’s an introduction to data cleaning in Pandas: Import Pandas: Before you start […]<\/p>\n","protected":false},"author":1,"featured_media":720,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20,19],"tags":[],"class_list":["post-702","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-panda","category-python"],"_links":{"self":[{"href":"https:\/\/learnwithneha.site\/index.php?rest_route=\/wp\/v2\/posts\/702","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/learnwithneha.site\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/learnwithneha.site\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/learnwithneha.site\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/learnwithneha.site\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=702"}],"version-history":[{"count":32,"href":"https:\/\/learnwithneha.site\/index.php?rest_route=\/wp\/v2\/posts\/702\/revisions"}],"predecessor-version":[{"id":741,"href":"https:\/\/learnwithneha.site\/index.php?rest_route=\/wp\/v2\/posts\/702\/revisions\/741"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/learnwithneha.site\/index.php?rest_route=\/wp\/v2\/media\/720"}],"wp:attachment":[{"href":"https:\/\/learnwithneha.site\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=702"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/learnwithneha.site\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=702"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/learnwithneha.site\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=702"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}