Power BI Python Tutorial | Python with Power BI | Power BI Tutorial | Edureka Rewind

Key Takeaways

good morning good afternoon and good evening guys based on the time zones you all are coming from so guys before we start with the session can you all please give me a quick information if you all can see my screen and hear me loud and clear as well perfect thank you for the confirmation everyone so my name is n Kia and I have been working in the S industry for more than 13 years now so today we have gathered for our discussion on top of how we can get started on using powerbi and how we can integrate that with python so we are going to first of all discuss on what python is now if you talk about the entire power discussion now the main agenda is we are going to to discuss on python on the prequest sets how we can use a python script to import data how we can use a python script to create visualization and all the possible drawbacks that we have so first of all we are going to discuss on python so python as we know is one of the easiest language to start with especially for those who are coming from non it backgrounds because python has the easiest syntax python has the easiest syntax as in if you compare python with Java for example if we are if you're trying to print any any statement in Java then there we have to write system.out.println and then only we can start printing the statement whereas if we talk about python then we have a simple playe English print and then we can use a statement to Simply print the any statement and then get started that's how easy it is and python as you know is a high level general purpose programming language which is extremely easy to pick up and it is well interpreted it is high level it also is offered as a general purpose language and because python has multiple use cases python can be well integrated in any use case python is completely platform independent and python has multiple inbuilt libraries that we use for multiple use cases for example if you are talking about image processing if we have we have libraries for image processing we have libraries for scientific calculations we have different trainings out there by using Python language now in terms of installation of python now to run Python scripts in powerb desktop we need to install python in a local machine and Python and python we know again is a powerbi python integration requires us to install two python packages pandas and matplot Link as well so these are the packages that we have to work on so now let's get started so currently we are going to use pycharm or we can use the python CLI as well so we can use this for downloading the entire python package in our system here you go and in case we want to use pycharm then we can use pycharm as pycharm is the most popular ID available by jet range so if we looking toop on core python then we can use the community version which is free and if you want to get started on using the professional version where we have where will be having the support for other languages as well like we have HTML JS and SQL support then we can go ahead and use the professional version depending upon the use case we can choose accordingly so when we install Pam it will is automatically going to make sure the python package is already configured that we can use for running the Python program so before we can see the integration here let's open up the powerbi desktop so powerbi we also need to have powerbi for this entire handson so powerp as we know is one of the most popular data visualization tool available just like we have Tableau we have powerbi so we can download the desktop version for powerbi in order to start using it here we can click on download from powerp desktop and if you're so this is available not for math system this is available able for Windows so this is going to open the powerbi store in powerbi application in Windows store and then we are going to get started on using that particular service so let's open up the powerb desktop that we already have the access to let's open it up so first of all we are looking uh we are going to look at how we can create a simple visualization by using powerbi as a part of our handson and then we are going to proceed further with all the other components step by step so now we have the entire powertop loaded so now we can open it up now before we can start using python we have to configure the python script that we can use that we can choose to get started of what or which particular interpreter of python or which particular version that we are going to use as a part of a Power Platform so first of all for configuring by then we have to click on the options and the configuration tab here so for that we can go to files and under options and settings we have options so from the given options we have to make sure that we are able to locate python scripting and then we have now from the from the open options here we have to locate python scripting and then we have to make sure we are chosing the right python home directory that we we are going to use as a part of our python integration so we have to make sure this is well integrated and in case we don't have that then we have to make sure that we are going to we going to use we are going to make sure we are the same the right ID is path is already defined So currently we are using the python 3.8 interpreter that we have configured and now once you want to continue using it we can simply click on okay and in case you want to see the det steps on how we can install and configure python we can click on option to the entire detail document as well so here we can click on okay now that means now we have successfully configured the entire components on power here so now we can start creating the code here in any of the other IDs or we can start coding directly in the powerp as well but as advisable it always always advisable to to create the code directly in the ID itself so that once we have the entire code created then we can import that code in bar we can do that so here we can so here we can open up our py charm so that we can create the script there in pycharm and then we can import that script in powerbi so let it open up and we can choose any of the version that we have the access to both in terms of PM and P as well let it open up so we can create create any new project and now we have before we can get started we also need to have Panda's Library also preconfigured that we are going to use that we may use it for creating multiple data frames as well so in case you don't have the integration for pandas already configured then we can install that by Panda's Library by using by going to the settings tab here and then choosing the interpretor for which we want to install the library here so we are going to install the library for python 3.8 that we are currently using so we can click on ADD section in the top right corner here we have ADD so here we can click on ADD and here we can specify if you're going to to use panas and here we can Define Paras Library we can search for it if you want to install any specific version for it we can specify the version and if you want to keep the default version as 1.05 we can click on install package so this is already going this that means by chance simply takes care of the entire installation for any package so that we don't have to install them manually one by one we can let pandas take care of the entire inst Solution on its own and then using pandas we can create any data frame and then we are going to imp to use these data frames also in our powerbi desktop now once we have configured that then we can start scripting on top of python so now we can start importing the P Library here and then we can start working on top of it so currently we are going to create a simple data frame by using python so we can import the library here first so here we can define import Bas as PD and then we are going to define the data frame by defining data and now data can be in any form for example suppose here we are going to Define data for the current data set such as the username and then the integer for example the name and the age for any person so here we can Define data frame so the first entry we can Define let's say we are going to add name and the ID for a person so your name can be let's say user or it can be any name for example say here we have Alex Define as one name we can Define the age of Alex such as 18 then we can create another entry here we can Define name as let's say John and then we can Define age as eight for John again we can Define another entry let's say we name as Wick and here we Define the age here let's suppose 27 this can be any age and So currently we are entering the age and name that we going to visualize as a part of this data thing that you're going to create now once we Define the data here then we can use data frame as DF and then from the P Library we are going to work on the data frame here we can Define data frame and then what data we are going to refer we are going to refer the data that we have already created and then here we are going to work on the columns and columns so whatever data we have entered we have to save that in the columns so Alexis Alex John W these are what these are name so here we can specify the First Column name first colum name as the name and then what exactly is 18 34 and 27 this is the age so we can Define it as H and then we can Define what kind of data it is so here we can Define d type so here we can Define d type D type refers to data frame like the data type and here we can Define that if data type is going to be float we can Define float and then if we are looking to print it then we can use the given data frame for printing that particular statement if you want and then once we are done we are going to use this script as well we going to use the script in powerbi so we can come back to our PBI desktop dashboard and to use a python script we have to click on get data and then we can choose any python script that SCE that we have to Define so if we click on get data source or other data source here we can choose python script so that we can enter the python in case you want to run any python script we can open the python script and here we can enter the script that we we have copied and once the entire script has been executed then we are going to look at the entire setup being done so let's change the version of python here just a moment as we have initiated a new library here so let's do one thing let's change the python engine here so we can go to options and here we have python we can choose the ID that we have currently configured let's confirm the in script let's confirm the enti interpretor first so here we have defined the entire package here so currently let's look at which particular interpretor we are using So currently we are this has floen just a moment so currently we are setting this up for a new interpreter that we are using for we can say we're using fresh for this entire interpret that we have created so here we are going to install a fresh installation of bandas because until and unless this live library is available for The Interpreter that we have chosen the python script in Pia is not going to be executed properly because whichever interpretor we choose we have to make sure because let's say if we are using the python script in powerbi so python in power is simply going to refer to the ID that we have selected here and the ID should have the library installed so as you can see the spers library has installed successfully for the current interpreter and now we can close it here we can see for this interpretor here we already have these different configurations already defo where we have pandas and N already configured so now we can apply it we can click on okay and here we can see the entire data frame being executed as per the requirement so as you can see the entire data frame has been presented to whatever we have defined as Alex John and Vic with the current age that we Define as a part of this library and now if we looking to use the same script in our PBI we can copy this up and then we can move on to our PBI desktop so we can come back to our PBI and we have to make sure that we choose this interpretor just a moment let's configure that so here we Define the the python ID in our users by our name then we have Define this in the folder and then once we Define it we can Define get data and here we can enter the python script that we have generated to execute the same thing the same script in powerp and we have to make sure that the same script the same interpreter is being used whatever we have structured so that we don't get any kind of Errors so once we enter the script here this is going to get connected to the same python that we had defined all right so as you can see here once we have the entire script executed here we can see the entire data frame and the current data which we have created in that script has now be imported as a part of python script right and now if you want to load it we can click on load and this entire data is being loaded as a part of python script that we have currently executed so let this entire video to be uploaded and then we will be able to see the list of fields available in the given data set so as you can see now you have age and then we have name being imported as a part of the Python screen that we have currently executed so basically in order to get started we have to make sure that we have the libraries installed in the python interpreter that we are going to use we have to make sure all the libraries are up and running and then we can come back to our Barby here we have to make sure that we are using the correct interpreter for python in which all the libraries are configured so for that we have to go to files under options we have python scripting options available so here we have to choose python scripting here we have to make sure that we are using the python home dietory where we have The Interpreter configured and then we can Define the python executable file so when we run any script this entire interpreter is going to be referred where it is going to look for any kind of library and all the scripting is going to be rendered by this particular interpreter corre so once we have configured that then we can click on get data and here we can choose python script as a part of data source so here we can choose python if you want we can search for the entire python data source python script and here we can enter the entire script for python that we have currently imported and we want to execute and then we can click on okay now let's suppose if we want to if we are going to create more sample data set because currently we have only two different data frames available so here we are looking to create more sample data frames then what we can do we can start defining more data frames let's say here we can Define for frame as age weight gender State children and the number of pets available that we can create multiple parameters for that so let's do one thing let's create the entire dat frame here itself so here currently we have defined data now let's add multiple data sets here let's add only here we can Define data frame okay let's do one thing let's create multiple data sets here so let's remove this data here for now let's Define data frame itself so here we are going to use data frame and in here we are going to Define each and every data pointers here so now let's say we are going to Define first name so let's say we Define first name here as F name first name so first name is we can Define any kind of name values now for first name we can Define multiple values if we want we can define B we can define c d f g so there can be multiple names defined here now we want to define the name of the the age as well for example say here let's say we Define another parameter as age as age and here let's find the value for age as well let's suppose here have someone is a is 24 then B is let's say 36 C is 14 D is 15 e uh okay we forgot e so here we can Define e so let's say e is 27 f is 64 and G is 45 so here we defined the different age parameters so here Define the age parameter here now next say we can Define multiple values let's say we have we are going to visualize weight as well then here we can Define the weight parameter and in weight we can define weight for each and every individual let's say here we Define weight as 75 as let's say 42 We No 4 will be too less for someone having 36 years of age so we can Define it as suppose 65 for 140 we can Define 42 for 15 we can Define let's say say 45 47 we can Define 78 for 64 we can Define 70 and for 45 we can Define let's say 76 in terms of weight same way we can define gender or say if you want to Define this for multiple Geographic areas as well as in cities as can as City itself so if you are going to add City based values so here we can Define City based value such as NYC we going to add a value for NYC and second value let's suppose for Sydney third value is for let's say Tokyo is for Delhi then we have let's say for Mumbai then we have for Singapore so how many values now we have we have one we have multiple values defined here 1 2 3 four five six and we have 1 2 3 4 5 6 7 so here we can Define one another city let's say we Define bang so here we have multiple cities defined as for the current value and data set that we are going to create so we can create this entire data frame locally or we can import this directly as well as for the requirement and let suppose here we want to Al Define children we also want to find States or multiple other parameters we can keep defining one by one hly we keep it for now and we can use the same print data frame so whatever we have we did here it is going to be printed for each and every individual here like we can see here let's do one thing let's import the entire script here back into the script section and here we click on okay to import this current data frame here so this is going to connect to the entire interpretor and then based on the given data frame we can see the list of all the data frames that has been impr and we can choose this one click on load so here we can see the entire parameters this was the earlier data frame and this a new data P containing the records for age City F name and we which we have currently imported and now we want to start if you want to start visualizing here we can use the element for python script available in as a part of visualization so either if you want we can use the same Vis like the same component for visualizing as a part of python tool right so now if you want to start visualizing on top of this one and here we have to make sure we are adding the values we adding the values here so for example whatever value we want to enter we can drag it in the same value section or we can customize in script as per the requirement right so let's suppose if you want to import all of these parameters here we can make a selection for all and if you want we can as you can see we have added all the parameters as a part of values as a part of values that we have currently added here and now if you want to start visualizing on top of it we can directly do that so once we have imported that here now we can start adding the script here itself as a part of scripting that we can see here so if you want we can add entire script here that we are going to visualize by using the M plot lib or we can use a cbor library as a part of statistical analysis and then we can get started so for example suppose if we want to use a simple scatter plot by using the the components as agent we then here we can start adding the script here let's say here we can Define the line as import Matt plot lib library for data visualization and from here we are going to use P plot as PLT and then we are going to define the data set data set. plot and then we can Define the kind now we are going to use a scatter plot here so here we can Define the kind as scatter plot so it is going to be a scatter plot graph and then we can Define the parameters such as on X we are going to map age that we had to find and on the y axis we are going to plot weight that we had Define so we want to see the distribution of wage and weight and we want we are going to plot it as a part of scatter plot graph and we can define the color let's say we want the color to be red that we can customize as as for the requirement as for the requirement we can simply Define the script and we can have it executed so if you want to visualize if you want to expand this entire code here we can see the entire distribution of age and weight has been shown as a part of the entire visualization that we have like how we have how we can visualize different sets of data as we can Define what kind of graph we are going to create and how we are going and if you're looking to plot the same component as a part of GRA gra as well then we can also Define that for example instead of scatter here we want to Define this as a part of line graph then we only have to change the entire type here from kind from scatter to line graph and we can see the entire vation that we are going to get here as a part of line graph instead of a scatter plot and we can Define you can combine multiple matrices as for the requirement we can Define them for example suppose if you want if you look to Define this as a component for bar graph if we want to Define this as histogram as bar graph then we can easily Define that let's say if you are looking to change this then we can change the kind from line to bar and then we can Define let's suppose here we want to change the color from red to blue as well we can Define it and as you can see here now we able to see the entire bar graph being plotted here so whatever color we want to change to we can define the color and then we can get started thank you so much for joining guys and have a great day ahead take care bye-bye