#22 Data Cleaning with Python Pandas | Data Science for Beginners in Tamil

Key Takeaways

Welcome back to this data science with machine learning course episode 22. last week Saturday because lot of values, lot of family years of careerap last week Saturday playlist data science career transition every week Saturday number. Okay. teaching videos Monday to Friday evening 6:30 p.m. Saturday night 9:00 p.m. I will I'm going to post this kind of series real time data science series college students I'm just open to give that opportunity. I'll directly recommend. So be prepared particularly we are looking for this data scientist engineer data analyst you all know why it is exactly market lot of things automated with respect to this data analyst jober You can feel free to apply for this. Sorry. Number one, second comment. I don't appreciate that kind of comments here. line. I don't get much impressed with this detail because I am a detail oriented person. Definitely it will be helpful for you and also for me to understand how deep you are going into the subject and learning data because But something which have taken the comm. So first episode find your best coach data science with machine learning playlist data scientist. You can just go there and watch different episodes different looping statement, function statement, condition statement, exceptional handling. A lot of things introduction different libraries pandas numpy m plot cond library. Python dat last week. I understand library deep data analyst opensource library such a powerful tool for every data analysis task last data frames series indexing selection data input and output CSV last two sessions last column alert. Input data cleaning techniques. Python program. Number one, data cleaning techniques. Fore details data file buffer as a beginner. So first tabular as a beginner level by default. By default particular value first So perform analysis repeated steps as a data powerful function. Find out the items sold in the restaurant. functions. Give me the list of top five items. Group function very important functions. Chapter two data cleaning. So chapter two data cleaning first data understanding. Okay. Business understanding business understanding the business understanding. Step number one. Step number two, data collection. Data collection. Step number one, business understanding. Second data collection. Third step in analysis on the data. Fourth step preparation. Data clean. Machine learning models. Machine learning models data preparation data scientist analyst numbers operations calculations detections and models data types types close open and particular function. This is an attribute attribute open but that will also return you something in the order ID in the quantity but it name item price. Okay. But now it last topelling items. Give me the list of top selling items. numberip number. So detlic. square item price. Okay. Order details functions. Okay. Okay. Sorry. Something. Okay. Multiple import. Replace to replace Cab by default. Okay. Replace values to replace with the value. Certain character Control Control Vift Replace values. Okay. Values in the series of data replace with the other values dynamically. This differs from updating. Okay. I lock I lock. Okay. Maybe in placeal true but still in the order. So still dollar replace string dot string function. Okay. properties and functions. Okay. Functions already functioning. function return a copy with all the occurrences of substring old. Okay. Old new. Okay. Old, new, because old CR V. Okay. Old is equal to double quotes new equal to in the particular function string string got an unexpected keyword. Old unexpected keyword argument. Okay. Wow. Because sometimes anyway which means in the particular operation. Okay. But data full operation float series has no [Music] for again. Okay. data type. Dat cannot convert series to float. Cannot convert series to series to float conversion overflow verification as type of marketing string. column to float as type in the particular function key. Next episode chain of methods. So explanation purpose. Okay, next problem. Okay. But still order details detecess. But in the particular operation in the column open square item column name double quotes in the right information update. So this is how we perform data cleaning operations. It max 44.25 already starting. Give me the list of top five selling items. Okay, find out the top five selling items uh individual individual revenue it made total total revenue of the top five items sold. Okay. Um maybe the least items same thing. Find out the comp. Find at least two more questions on the same data set. So I I believe that first thing I'm trying to simplify detail step by session. I have to make this Max three months. So two and a half months already fourth week fourth week or third week. So uh I think it is already fourth week but in the session what is it something that you're taking from this whether it is easy for you to understand how how easy it is for you it will be helpful for me to continue give this kind of content. So keep following and I would deserve like that's okay. Fine. That's okay. But I'm feeling happy. I'm feeling good. But that is also kind of one kind of contribution which can do it for me and also for you and also for that particular person to grow. This is your a John. Let's make a simplified. See you all in the next episode. Bye. Cheers. [Music]