From 1ac3f9c104ef7d6c945ea3277d3e13e730dfb035 Mon Sep 17 00:00:00 2001 From: INDRASHIS PAUL Date: Tue, 5 Oct 2021 19:18:47 +0530 Subject: [PATCH] Update previous lesson link --- 2-Working-With-Data/08-data-preparation/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/2-Working-With-Data/08-data-preparation/README.md b/2-Working-With-Data/08-data-preparation/README.md index 58c2e528..29534354 100644 --- a/2-Working-With-Data/08-data-preparation/README.md +++ b/2-Working-With-Data/08-data-preparation/README.md @@ -31,7 +31,7 @@ Depending on its source, raw data may contain some inconsistencies that will cau ## Exploring DataFrame information > **Learning goal:** By the end of this subsection, you should be comfortable finding general information about the data stored in pandas DataFrames. -Once you have loaded your data into pandas, it will more likely than not be in a DataFrame(refer to the previous [lesson](https://github.com/IndraP24/Data-Science-For-Beginners/tree/main/2-Working-With-Data/07-python#dataframe) for detailed overview). However, if the data set in your DataFrame has 60,000 rows and 400 columns, how do you even begin to get a sense of what you're working with? Fortunately, [pandas](https://pandas.pydata.org/) provides some convenient tools to quickly look at overall information about a DataFrame in addition to the first few and last few rows. +Once you have loaded your data into pandas, it will more likely than not be in a DataFrame(refer to the previous [lesson](https://github.com/microsoft/Data-Science-For-Beginners/tree/main/2-Working-With-Data/07-python#dataframe) for detailed overview). However, if the data set in your DataFrame has 60,000 rows and 400 columns, how do you even begin to get a sense of what you're working with? Fortunately, [pandas](https://pandas.pydata.org/) provides some convenient tools to quickly look at overall information about a DataFrame in addition to the first few and last few rows. In order to explore this functionality, we will import the Python scikit-learn library and use an iconic dataset: the **Iris data set**.