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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

2 Top Python Libraries to Create ML model

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To Create a Model of Machine Learning in Python, you need TWO libraries. One is 'NUMPY' and the other one is 'PANDAS'. 2 Top Libraries You Need To Build a model of Machine learning you need the right kind of data. So, use the data for your project should be refined. Else, it will not produce correct results. The prime steps are Data Analysis and Data Preprocessing. NUMPY - It has the capabilities of Calculations. PANDAS- It has the capabilities of Data processing. How Install Python Machine Learning Libraries  import  NumPy as np # linear algebra import pandas as PD # data processing, CSV file I/O (e.g. PD.read_csv) How to Check NumPy/Pandas installed After '.' you need to give double underscore on both sides of the version.  How Many Types of Data You Need You need two types of data. One is data to build a model and the other one is data you need to test the model. Raw data Evaluate-data How to Build a Model Flowchart I have given a f