Featured Post

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

Data analysis report these are example queries to use on final data

Data analysis
The role of data analysis will come into picture, once you have cleaned and filter the raw unstructured data. The next stage is called analysis. Your success of data analysis project is based preparing highly informative final report.

What could you investigate with data

To prepare analysis report, you need to ask some intelligent questions. These are example questions you can use. Based on your questions, you  need to prepare SQL queries to get the desired report or dashboard from your final data or cleaned data. 

The report or dashboard should be such that it should improve client business.
Let us use some case study on world bank data, what are the questions come into mind:

  1.  How much (in USD) is spent on healthcare in total in each country? 
  2. How much (in USD) is spent per capita in each country?
  3.  In which country is the most spent per person?
  4.  In which country is the least spent? 
  5. What is the average for each continent?
  6. For the world?
  7. What is the relationship between public and private health expenditure in each country? 
  8. Where do citizens spend more (private expenditure)? 
  9. Where does the state spend more (public expenditure)?
  10.  Is there a relationship between expenditure on healthcare and average life expectancy? 
  11. Does it make any difference if the expenditure is public or private?  
Read more here


Popular posts from this blog

Explained Ideal Structure of Python Class

How to Check Kafka Available Brokers

6 Python file Methods Real Usage