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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

The Exclusive Way to Declare Variables in Oracle Procedure

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There are four data types in PLSQL. Those are Numeric, Char, Boolean, and Date/Time. Each data type and its features are demonstrated. And explained how to declare variables in PLSQL procedure. Data types Here are the four popular data types in PLSQL. 1. Numeric DEC, DECIMAL, and NUMERIC are used to declare fixed-point numbers with a precision of a maximum of 38 decimal digits. INTEGER, INT , and SMALLINT declare integers with a maximum precision of 38 digits. 2. Char Char and Varchar data types support storing data of 1 t0 2000 bytes. The VARCHAR2 supports 1 to 4000 bytes of data. The VARCHAR and VARCHAR2 release the unused space in memory,  3. Date/Time The range for the Date is from 01-Jan-4712 BC to 31-DEC-9999. It stores the data in date format DD-MON-YYYY. The value is written in single quotes. 4. Boolean BOOLEAN datatype stores logical values and can be either TRUE or FALSE. Declare variables The Declare block in PL/SQL is reserved for variable declaration. The code between beg

Python Supports These 5 Native Data types

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Python supports five native data types. The Data types are such that a Programmer can use to write the logic and get the output. Many beginners may not aware of native data types. So I am adding a short note on that here. Native means as is Python supported data types. Python Five Key Native Data Types Python Native Data Types In Python, you can find five types of native data types. Here is a quick list for you. Those are Number, String, List, Tuple, Set, and Dictionary. 1. Number For all the numeric values,  you can use this data type. 2. String It handles all Characters, Special-symbols, and Alphanumeric values. 3. List It is something like sequential data. A program can do Sort, Merge, etc. on this data. 4. Tuple Data is a little different from the List. 5. Set This kind of Data-type helps you to do set operations. Those are like Intersection, Difference, etc. 6. Dictionary Here, the Dictionary something like a group of List kinds of data. But, each value has a key associated with i