Showing posts with the label dictionary for loop

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How to Check Column Nulls and Replace: Pandas

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

Print Dictionary Values Simplified Logic

Here's for loop logic that says how to use Dictionary to get its data. I will present here how to use it as input In for loop. You can also call Dictionary as Map, Hash, or Associative array. Print dictionary values Below is my example. I have created a simple Dictionary called 'store.' Then, I will get its data using for-loop. Here's my previous post Python -  How to Lookup Dictionary By Key . Dictionary example Store = { "rao" : 1, "srini' : 2} For-loop logic for key in store:       print (key, store[key]) Laptop batteries can last longer if you charge them up to only 80% instead of the full 100%. - By Real-time result The execution of for loop showed here. It's much simple. Just use the code as I did. You'll get the desired result quickly. References Python for Everybody: Exploring Data in Python 3 SOFT SKILLS for a BIG IMPACT: Banish Self-Doubt, Improve Workplace Ethics