Python Data Science Tutorial #17 - Pandas Queries

Key Takeaways

what is going on guys welcome to this peyten tutorial series for data science in today's episode we're going to learn how to query data out of data frames because as we already mentioned data frames are very similar to SQL tables in an SQL you can just query data out off the tables of the database and we're going to do the same thing in pandas today with data frames and also we're going to take a look at how to read from CSV files into data frames so let us get into the code so we start by importing pandas as PD no surprise here and today we're not going to create our dictionary and then transform it into a data frame what we're going to do is we're going to create a CSV file and then import that CSV file into pandas so I'm going to click here a right-click and say new file and just name it people dot CSV and here we're just going to provide SSN and we're going to separate all things by commas so this end then name age and height and I'm going to say okay one Anna H is 45 height is 167 then to John 65 years old yeah they're always changing their social security number their height or age everything just a name stays the same [Music] 188 five could be pop eise forty five also and 178 and last but not least social security number eight Mike and he's 56 or let's make him a little bit younger 26 ah and he's 167 okay we have that budget value already Oh 169 so this is now our CSV file and usually CSV is a very popular format for God for saving data for also uploading data sets so we should know how to deal with that and what we're to do now so I'm just going to say D F equals P D re CSV and providing the people dot CSV file name and we can also specify a delimiter to be a comma of course you don't have to choose comma I can also go ahead and say R or use semicolons or caps is also valid [Music] separator or delimiter and to see if that works we're just going to print a data frame should work doesn't work the limit here the limiter sorry then it should work yeah as conceit works the only thing that we need to do now is to set the index so DF dot set index is the SSN column and in place equals true should work yeah now we have a data set as we know it and as I said today we're going to learn how to query data out of that data set so how can we say give me all the columns that have an H higher than X Y Z or that have a height between this and that because this is what we can do in SQL statements we can say select a name from a data frame where H is greater than 40 for example this would be an SQL statement and we can do the same things here in data frames in a different way of course so what I'm going to say is I'm just going to say print D F dot lock for location so we need to use the lock keyword and in here we're going to open up square brackets and say DF and then we're going to choose the column that we want to query for or that we want to check or make a condition on so I'm going to say give me all the rows the data rows that have an 8 for example that is equal to 45 and when I print that you'll see that we have two entries here with the age 45 and I get Anna and Bob as a result now of course what I can also do is I can just say give me all the ages that are greater than 45 and this would be only John and if I say greater or equal to it would give me John Anna and Bob these two should be yeah of course what I can do is I can also put this into parenthesis here and then just use the ant symbol here and just say okay the H has to be greater or equal to 45 but the height has to also be greater than 170 centimeters so I'm going to say height is greater than 170 and this of course eliminates Anna from this list here because Anna is 167 centimeter size so we only have John and Bob left and now what I can also do is I can just go ahead at the end here and say okay which columns am I even interested in I don't want to know the height and H maybe or anything but the social security numbers so I can just go ahead and say social security number or just give me the name so give me the same results but only give me the names so I get John and Bob now of course the indexes are always part of that because it's the primary key if you want to compare it with SQL structures so that is basically how you query data out off data frames so that's it for this video and I also think that's it for the data science series because now we covered almost everything that you need to know about data science of course if I find some topic that I haven't covered yet that I want to cover in the future I might make some extra episodes but I think that for now we're done with the data science tutorials and we can continue on with the machine learning tutorials so now we're getting into my favorite part of Python programming my favorite field of computer science machine learning and I hope you enjoyed this series I hope you enjoyed this tutorial seer if so hit the like button to support this channel and of course feel free to ask questions and give feedback in the comment section down below and of course subscribe to this channel if you want to see more future videos so thank you very much for watching see you in the next video and bye [Music]