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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

SQL Tester Ideas DATE, Numeric, CHAR, NULL

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I have shared top SQL Date functions along with Numeric, CHAR and NULL functions. List of Built-in Functions DATE-TIME functions Numeric functions Char functions Null-related functions 1. DATE/TIME functions SELECT p_code, launch_dt, CURRENT_DATE FROM product; CURRENT_DATE returns the CURRENT date. SELECT p_code, To_char(launch_dt, 'DD MONTH YYYY') reformatted_dt FROM product; TO_CHAR FUNCTION returns date IN char format. 2. Numeric functions SELECT p_code, price, (price - 20), Abs(price - 20.00) FROM product; ABS - FUNCTION returns the absolute value SELECT p_code, price, Round (price, 1) FROM product; ROUND FUNCTION - round TO 1 digit. SELECT p_code, price, Sign(price - 15) FROM product; SIGN FUNCTION - it returns the sign SELECT p_code, price, Trunc(price, 1) FROM product; TRUNC FUNCTION - truncates TO a certain number OF decimal places. 3. CHAR functions SELE