Mido: A Powerful Tool for Spreadsheet Analysis

As we began our analysis, we started with two separate data sets: one containing information about free users and another containing information about paid users. We merged these two data sets together using mido's merge functionality, which allowed us to combine user info and user visits into a new data set. This powerful tool enabled us to perform complex analyses quickly and efficiently.

Mido generates Python code that corresponds to our edits in the spreadsheet, allowing us to use a spreadsheet as a source of power for building quick, powerful, and repeatable analyses. With mido, we can add new columns to our data, perform calculations using spreadsheet formulas, and create pivot tables to break down complex data sets.

The first thing we did was merge our two data sets together by clicking the "merge" button in mido. This created a new data set that contained all of the information from both of the previous data sets, but now it was all in one column for a single user. We could see all of the information about them in this combined data set.

Next, we added a new column to our data to perform a calculation. In this column, we wrote any spreadsheet formula that we would use in Excel or Google Sheets. The powerful part of mido is that it supports all commonly used spreadsheet functions and can rename columns to keep our spreadsheet clean behind the scenes.

With our data now cleaned up, we could move on to using a pivot table to break down free versus paid users. We selected "user type" as the rows in the pivot table, since we were interested in comparing the number of weekend and weekday visits of these users. By aggregating weekday visits by mean and weekend visits by mean, we could see how their website-visit habits differed.

Behind the scenes, mido generates Python code that corresponds to our edits in the spreadsheet. We didn't have to do anything except edit the spreadsheet, and mido took care of generating the Python code for us. When we clicked "group" in the pivot table, mido generated more Python code behind the scenes.

Our analysis showed that paid users tended to visit a little bit more than free users both during the weekday and on the weekend. We also saw that as accounts got older, the number of weekday visits stayed relatively the same while the number of weekend visits decreased dramatically.

To finish our analysis, we filtered down to just paid users and sorted our data by account age. This allowed us to see if there was any relationship between how long someone had been a paid user and how many visits they took. We verified that total visits were going down over time using another pivot table.

When we repeated this analysis on new data, we could simply click the "repeat saved analysis" button and select our previous analysis. Mido worked its magic, generating the Python code behind the scenes to quickly and reliably replay our analysis and save us time.

If you're interested in checking out mido, you can visit their website at trimeto.io to get early access. We also want to encourage everyone who's finding value in this video to like it, subscribe if they haven't yet done so, and hit the notification bell to be notified of our next video. As always, the best way to learn data science is to do data science itself.

As we wrapped up our analysis, we realized that mido is a powerful tool for spreadsheet analysis. It allows us to build quick, powerful, and repeatable analyses using a spreadsheet as a source of power. With mido, we can perform complex calculations, create pivot tables, and generate Python code behind the scenes. We hope this video has shown you the potential of mido and encouraged you to explore it further.

In the meantime, please check out these videos and subscribe if you haven't already. If you're interested in learning more about data science, we invite you to join us on this journey. Thank you for watching, and we'll see you in our next video.

"WEBVTTKind: captionsLanguage: enin this video i have the privilege of inviting nate from the middle developer team to give us a short demonstration of how to use mido in action so mido is a python library that will allow you to have spreadsheet functionality right inside the jupiter notebook and so the topics covered today will include how you can merge data frames how you could perform commonly used spreadsheet functions how to filter data how to pivot the data how you could save the analysis that you are doing for reuse in the future and best of all mido will be able to generate the corresponding python code as you edit using the point and click interface of the mitel and so without further ado we're starting right now hey i'm nate i'll be showing you mido a fast repeatable spreadsheet that's built for all of your data analysis and reporting needs mito is different from excel in google sheets because it turns all of your edits into professional python code making it super easy to change audit and rerun your data analyses so let's get started we've already got a mido notebook up and ready to go at the top you'll see all the python code we need to write during the entire analysis let's get started by displaying a miter sheet once the sheet is displayed we can start exploring our data it seems like we've got two data sets here user info contains information about users including their id whether or not they're a paid or a free user as well as how old their account is user visits seems to be from a different data source it's got an account id as well but also the total number of visits they've taken to our website ever the number of visits they've made during a weekday as well as when they started visiting our website we'll now use mido to understand the difference in user behavior depending on whether or not the user is a free or a paid user the first thing that we can do is we can merge these two data sets together because they share a user id column we can click merge and using mido's merge functionality we can combine user info and user visits upon the shared merge key into a new data set when we click merge two things happened first a new data set was created this contains all of the information from both of the previous data sets but now it's all in one line so for a single user we can see all of the information about them second and this is the powerful part mito generates python code that corresponds to your edit where we did emerge in the sheet we got a merge in the code as we'll show in the rest of this demo this generated python code will allow you to use a spreadsheet to build quick powerful and repeatable spreadsheet analyses now that we've got all of our data in one place let's figure out how many visits are coming from free versus paid users on different days of the week first we can add a new column to our data to perform a calculation in this column we can write any spreadsheet formula that we would in excel or google sheets here it's just a simple subtraction where we support all commonly used spreadsheet functions we can also rename our column to keep our spreadsheet clean behind the scenes mido continues to generate production-ready python code that corresponds to those edits all i had to do was edit the spreadsheet next we can use a powerful part of any spreadsheet analysis a pivot table we will use a pivot table to break down free versus paid users and we'll figure out exactly how their website visiting habits differ after clicking the group button we'll transform the data by selecting our user type as the rows since we're interested in comparing the number of weekend and weekday visits of these users we can choose to aggregate weekday visits by mean and weekend visits by mean as well and then we'll click group we can check our newly generated pivot table to observe that paid users end up visiting actually just a little bit more than free users both during the weekday and on the weekend again mito generates python code that corresponds to this pivot behind the scenes we'll finish our analysis by seeing if there's any relationship between how long someone has paid to be a user and how many visits they take to do so we'll first filter just down to paid users now let's sort our data by account age to see if we can see any relationship interesting it seems like total visits are going down over time let's verify that with another pivot again since we're interested in breaking down by account age we can select that as rows we can select weekday visits to calculate the average and again weekend visits to calculate the average and click group and if we look at our new data frame it seems like as accounts get older the number of weekday visits stays relatively the same while the number of weekend visits decreases dramatically awesome let's wrap this analysis here i think we've got some really good insights to share with the mito team now that we've completed this analysis we can save it saving an analysis allows us to reuse it at any point in the future on new data because mido is powered by python you only need to do any analysis task once and you can replay it as many times as you want let's just save this as visits analysis now let's imagine a week passes and we get some new data about our users in a similar format to before all we have to do to repeat our analysis is click the repeat saved analysis button select our visits analysis and click replay and mido works its magic we can check out the same pivot tables with our new data and it looks like the weekend visits trend changes a little bit on this new data set behind the scenes mito uses the generated python code below to quickly and reliably replay your analysis and save you time if you're interested in checking out the product you can visit our website at trimeto.io to get early access we can't wait to speed up your analysis workflow thanks thanks nate for the awesome demonstration and if you're finding value in this video please give it a thumbs up subscribe if you haven't yet done so hit on the notification bell in order to be notified of the next video and as always the best way to learn data science is to do data science and please enjoy the journey thank you for watching please like subscribe and share and i'll see you in the next one but in the meantime please check out these videosin this video i have the privilege of inviting nate from the middle developer team to give us a short demonstration of how to use mido in action so mido is a python library that will allow you to have spreadsheet functionality right inside the jupiter notebook and so the topics covered today will include how you can merge data frames how you could perform commonly used spreadsheet functions how to filter data how to pivot the data how you could save the analysis that you are doing for reuse in the future and best of all mido will be able to generate the corresponding python code as you edit using the point and click interface of the mitel and so without further ado we're starting right now hey i'm nate i'll be showing you mido a fast repeatable spreadsheet that's built for all of your data analysis and reporting needs mito is different from excel in google sheets because it turns all of your edits into professional python code making it super easy to change audit and rerun your data analyses so let's get started we've already got a mido notebook up and ready to go at the top you'll see all the python code we need to write during the entire analysis let's get started by displaying a miter sheet once the sheet is displayed we can start exploring our data it seems like we've got two data sets here user info contains information about users including their id whether or not they're a paid or a free user as well as how old their account is user visits seems to be from a different data source it's got an account id as well but also the total number of visits they've taken to our website ever the number of visits they've made during a weekday as well as when they started visiting our website we'll now use mido to understand the difference in user behavior depending on whether or not the user is a free or a paid user the first thing that we can do is we can merge these two data sets together because they share a user id column we can click merge and using mido's merge functionality we can combine user info and user visits upon the shared merge key into a new data set when we click merge two things happened first a new data set was created this contains all of the information from both of the previous data sets but now it's all in one line so for a single user we can see all of the information about them second and this is the powerful part mito generates python code that corresponds to your edit where we did emerge in the sheet we got a merge in the code as we'll show in the rest of this demo this generated python code will allow you to use a spreadsheet to build quick powerful and repeatable spreadsheet analyses now that we've got all of our data in one place let's figure out how many visits are coming from free versus paid users on different days of the week first we can add a new column to our data to perform a calculation in this column we can write any spreadsheet formula that we would in excel or google sheets here it's just a simple subtraction where we support all commonly used spreadsheet functions we can also rename our column to keep our spreadsheet clean behind the scenes mido continues to generate production-ready python code that corresponds to those edits all i had to do was edit the spreadsheet next we can use a powerful part of any spreadsheet analysis a pivot table we will use a pivot table to break down free versus paid users and we'll figure out exactly how their website visiting habits differ after clicking the group button we'll transform the data by selecting our user type as the rows since we're interested in comparing the number of weekend and weekday visits of these users we can choose to aggregate weekday visits by mean and weekend visits by mean as well and then we'll click group we can check our newly generated pivot table to observe that paid users end up visiting actually just a little bit more than free users both during the weekday and on the weekend again mito generates python code that corresponds to this pivot behind the scenes we'll finish our analysis by seeing if there's any relationship between how long someone has paid to be a user and how many visits they take to do so we'll first filter just down to paid users now let's sort our data by account age to see if we can see any relationship interesting it seems like total visits are going down over time let's verify that with another pivot again since we're interested in breaking down by account age we can select that as rows we can select weekday visits to calculate the average and again weekend visits to calculate the average and click group and if we look at our new data frame it seems like as accounts get older the number of weekday visits stays relatively the same while the number of weekend visits decreases dramatically awesome let's wrap this analysis here i think we've got some really good insights to share with the mito team now that we've completed this analysis we can save it saving an analysis allows us to reuse it at any point in the future on new data because mido is powered by python you only need to do any analysis task once and you can replay it as many times as you want let's just save this as visits analysis now let's imagine a week passes and we get some new data about our users in a similar format to before all we have to do to repeat our analysis is click the repeat saved analysis button select our visits analysis and click replay and mido works its magic we can check out the same pivot tables with our new data and it looks like the weekend visits trend changes a little bit on this new data set behind the scenes mito uses the generated python code below to quickly and reliably replay your analysis and save you time if you're interested in checking out the product you can visit our website at trimeto.io to get early access we can't wait to speed up your analysis workflow thanks thanks nate for the awesome demonstration and if you're finding value in this video please give it a thumbs up subscribe if you haven't yet done so hit on the notification bell in order to be notified of the next video and as always the best way to learn data science is to do data science and please enjoy the journey thank you for watching please like subscribe and share and i'll see you in the next one but in the meantime please check out these videos\n"