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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

4 Built-in functions in SQL Explained Superbly

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Here're four types of built-in functions in SQL. You don't need to create these functions, and these come with your SQL. I am discussing today the  SQL functions List . SQL functions DATE-TIME functions Numeric functions Char functions Null-related functions 1. DATE-TIME functions   These are useful to get DATE and Time. Also, you can covert the DATE and TIME to Char. These are TO_CHAR, CURRENT_DATE, and CURRENT_TIME. 2. Numeric Functions   These functions you can use for numeric calculations. Those are TRUNC, SIGN, ROUND, ABS. 3. Char Functions   To handle string-related tasks you can use CHAR functions. The CHAR functions are like SUBSTR, CONCAT, LENGTH. 4. NULL related functions   To handle null values you can use different functions. Those are COALESCE, NVL, NULLIF This post covered all your answers for the SQL functions list, SQL built-in functions in Oracle, and SQL functions in any DBMS. Also, Read SQL tips to improve Query performance Summar