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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

What is so Trendy in Data Visualization and Reporting

Data Visualization: Data visualization is the process that defines any effort to assist people to understand the importance of data by placing it in a visual context. 

Patterns, trends, and correlations that might be missed in text-based data can be represented and identified with data visualization software.

It is a graphical representation of numerical data. This is one of the Hot skills in the market, you will get the highest salary.

Types of data visualization

Visual Reporting

  1. Visual reporting uses charts and graphics to represent business performance, usually defined by metrics and time-series information.
  2. The best dashboards and scorecards enable the users to drill down one or more levels to view more detailed information about a metric
  3. A dashboard is a visual exception report that signifies the ambiguities in performances using visualization techniques

Visual Analysis

  1. Visual-analysis allows users to visually explore the data to observe the data and discover new insights 
  2. Visual-analysis offers a higher degree of data interactivity 
  3. Users can visually filter, compare, and correlate the data at the speed of thought incorporating forecasting, modeling, and statistical analysis 
  4. Data Visualization Representations

Business Intelligence Dashboard

  1. A business intelligence dashboard is a data visualization tool that represents the current status of metrics and key performance indicators for an enterprise 
  2. Dashboards combine and arrange numbers, metrics and sometimes performance scorecards on a single screen. They can be customized for a specific role and display metrics targeted for a single point of view or department 
  3. Microsoft and Oracle are some of the vendors for business intelligence dashboards. 
  4. BI dashboards can also be created through other business applications, such as Excel. They are sometimes referred to as enterprise dashboards. 

Performance Scorecard

  1. It is a graphical representation of the progress over time of some entity, such as an enterprise, an employee or a business unit that functions towards some specified goal 
  2. The important factors of performance scorecards are targets and key performance indicators (KPIs). 
  3. KPIs are the metrics that are used to evaluate factors that are essential for the success of an organization 
  4. The main difference between a business intelligence dashboard and a performance scorecard is that a business intelligence dashboard, like the dashboard of a car, indicates the status at a particular point in time. A performance scorecard displays the progress over time towards specific goals


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