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How to Check Column Nulls and Replace: Pandas

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Here is a post that shows how to count Nulls and replace them with the value you want in the Pandas Dataframe. We have explained the process in two steps - Counting and Replacing the Null values. Count null values (column-wise) in Pandas ## count null values column-wise null_counts = df.isnull(). sum() print(null_counts) ``` Output: ``` Column1    1 Column2    1 Column3    5 dtype: int64 ``` In the above code, we first create a sample Pandas DataFrame `df` with some null values. Then, we use the `isnull()` function to create a DataFrame of the same shape as `df`, where each element is a boolean value indicating whether that element is null or not. Finally, we use the `sum()` function to count the number of null values in each column of the resulting DataFrame. The output shows the count of null values column-wise. to count null values column-wise: ``` df.isnull().sum() ``` ##Code snippet to count null values row-wise: ``` df.isnull().sum(axis=1) ``` In the above code, `df` is the Panda

Top Teradata Course details that you need to learn

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Teradata is most popular database among data warehousing projects. You will learn Teradata from any institute you want. My post intention is you just take a look on course contents you need to learn. Course Contents You Need to Look Before You Start Related: Top Data warehousing Interview Questions Introduction to Teradata Data warehousing concepts and SCD’s OLTP & OLAP Teradata Architecture & Physical Design Teradata Vs. Other RDBMS BYNETPEs AMPs Vprocs Clique Cluster Data Storage Data Distribution Data Access Teradata Space Management Fault Tolerance Data Protection Teradata Indexes and Performance Tuning and Optimization UPI – Unique Primary Index NUPI – Non Unique Primary Index USI – Unique Secondary Index NUSI – Non Unique Secondary Index PPI – Partition Primary Index MLPPI – Multilevel Partition Primary Index STJI – Single Table Join Index MTJI – Multi Table Join Index AJI – Aggregate Join Index Global Temporary Tables and Vola