Interative Data Analysis in Pandas | #53 of 53: The Complete Pandas Course
The 12th Tip I want to show you is one amazing tool for interactive data frame visualization as well as analysis. The tools name is detail, you need to first install it in order to use it..
Let's see how to install and use it.
🔹 Tips and Tricks on Interactive Dataframe Visualization and Analysis in Python Pandas.
Once installed, it's very easy to access the data frame and visualize your data frame assets. Now, this is the command to install it once you install you can import it I have already imported and loaded the data frame also, just through one single function, you can invoke all of these analysis not just this more of such analysis is present.
That is analyzing missing values, summary statistic, analyzing duplicates, variance report highlighting missing values all these, let's have a look at it. On running detail dot show pass your df to it. This provides a view that looks something like this.
This is your data frame view. right you can see some of the columns or in fact all of the columns and rows in your data frame everything is present here. Alright, now, go here. If you click here, this menu comes up. Inside this click on detail, actions, visualize highlight settings, all these are various different functions.
To show all of these functions in one single menu, you can click on this play button here, all of those menu items are present in one single menu over here. Let's go over this. Now to view this data frame. Here we have a constraint view right for this data frame.
To view this in a new browser window, you can open the entire data frame in a new browser window like this. Now let's look at this, we have created a new window, let's click on describe this intern opens a new window. This gives you a more detailed description of each of that variables or columns that you have in your data set.
You have the describe we have histograms value count QQ plot more statistical plots. Then you have passenger ID passenger ID describes it describes the unique values, outliers, no outliers, decades are like this, you have descriptions of each and every column there.
Next, you have custom filter using this you can filter whatever you whatever value you want, whatever rows that you want to filter, you can filter it, you can create new columns using bulk columns, merge and stack, summarize data. Let's look at this.
Let me know in the comments section if you have any questions!
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