#18 Python Dictionary Explained with Real-Life Data Examples | Data Science for Beginners in Tamil

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Number that is really great because our goal is to make AI simplified. assumption. So, happier section. So let's buckle up and be ready. Let's learn the four data structures of Python last data structure dictionary key value. So just buckle up and be ready. Fourth one dictionaries. In the dictionary data structure always we will call it as it is a key value pair back in 2016 but complex in the particular teaching. Okay. for it to particular most of the color particular information. So particular entry either rows either rows or columns empty dictionary. Okay. Open and close curly braces. Okay. Can't contain duplicate keys but can contain duplicate values. Okay. Empty empty number four. Okay. Next number right open close sorry type of this particular variable is Okay. For example, 89 98 89 98 students. Student marks. data type of student marks. This is coming in set. What is the difference? Max first value. Okay. Maybe particular subject maybe science science dictionaries twodimensional because multiple columns and column but it's Okay. technical particular set example. foreign open. So first potato. Okay. Tomato. Okay. Apple.5 [Music] maybe items to buy level writing. First step items. Okay. Items to buy four. Okay. Control Ctrl C type and open and close V always we call it as key values by default because already duplicate values. duplicate values but it will allow duplicate keys. Duplicate keys. But later. So in dictionary don't put duplicate keys but you can create duplicate values which means duplicate because don't put duplicate keys inside this dictionary but you can put duplicate values items to val Because alwaysice unhashable indexing not possible. Slicing is also not possible. But indices all the items from the data structure. Okay. Empty dictionary values once assigned to this particular dictionary. It can be changed or updated any time in the future. In the particular particular number items to buy shift open and close and close function function Fine. The particular items to buy potato five numbers the potato tomatoes items to buy. Dots items to buy. Keys functions open and close. Shift tab. Upper values. Key value Python data structures. Python library here. We can do something great. The potato cemp import pandas as pd one of the data structure. Data frame data frame data structure data potentially heterogeneous tabular data supply data structure also contains labeled axis rows and columns. Arithmetic operations align on both rows and columns can be thought. Okay. Okay. Parameters items. Okay. If using all scalar values you must pass an indexal index to use for resulting frame index. Okay. index must be called with a collection of some kind of zero was passed in the items to buy. Okay, fine. We need to have concept. Okay. Complexity students the particular student marks student marks equal to dictionary first particular let's say um class one class math Math math subject student marks and everything class 678 89 93 Okay. Expected column expected after more than one. But values more than I need to knock the door of what? Values more than one. I need to knock the door of data structures. list. It is going to be more than one. duplicate values. So I have to knock the door of listable options in the multiple values. I will be taking inside square bracket which is nothing but list. data. I'm going to pass math student marks. always in the particular index index numbers of the students key First, second student maybe. Third student maybe J. Okay. Fine. for 1 2 3 4 5 shift meaning in the particular student math subject Okay. Science level shift sorry again. Shift enter. Okay. So this is how you can create a data frame. Okay. value because if using all scalar values you must pass an index multiple values row. So that is when I will be knocking the door of dictionaries. Okay. in the particular dictionary properties. So dictionary onedimensional two dimensional of course it is twodimensional because rows information you can store in rows and column format heterogeneous data type because it can be changed anytime in the future. Indexing and slicing possible. It's this not possible. Indexing and slicing is not possible. Okay. Allows duplicate values. Don't don't don't create duplicate keys. But you can create duplicate values. problem right thinking Okay, but I feel that you all are enjoying this particular session because your comments is something which I'm reading getting more energy. Okay, the end. So, Python data structures just try to create create three data frames from dictionary or dictionary information. Try to create for Python data structure. How do you choose between list versus sets versus tpple versus dictionary? Okay. comment section but try to answer to this particular question I'll try to appreciate you by mentioning your names again I'll remind you the efficient way of learning step number one I do you see step number two I do you do third step you do I see so I hope this particular session is something useful to Python library how this pandas can be useful for data analysis. So in the particular episode, I would deserve a like. that is something on your particular side. Okay, this is your a John. Let's make a simplified. See you all in the next episode. Bye. Cheers. [Music]