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[no audio]

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Friends, here we are going to work with CSV files using Python.

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So first of all, what is CSV?

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See guys simply, CSV is a Comma Separated Values.

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That means whatever the values you have in a CSV file

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they all are separated by a comma, or separator is comma,

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or delimiter is comma. Separator or delimiter is same, right.

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Fine. Now why we are using this? So you are going to use this

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just to store tabular type of data,

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such as your Excel or database data. Of course, we can store

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our data as a tabular form in your Excel sheets as well.

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But compared to excel sheets, CSV is the simple way to store

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your tabular type of data.

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Let me do one thing.

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First of all, I am going to open a simple file.

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Let me open a file called, simply any text file

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I am going to open it.

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Right. Fine. See that.

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Let me open it first.

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See by default your CSV data is separated with comma. So

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basically CSV, you can assume that CSV is like your Excel sheet,

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or tabular data. So the tabular data is nothing but you have

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rows and columns. Your data,

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your data is like a rows and column.

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Let's say I have suppose, column as serial number,

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name, suppose salary, then skill, so I am going to store in

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this way. Suppose

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let's say 'John', 'Python',

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sorry. 'salary', right. Some $2000.

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Let's say 'Python'. Then I have 'Jason',

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then $1000,

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then I have suppose, Bash.

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Let me save it as, as a CSV file.

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Some 'info.csv', that's it.

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So I saved your file as '.csv' extension, as a CSV file.

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See now this is your CSV file.

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I can open this CSV file with any 'Notepad', right?

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See that. Your data

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is there as it is, or by default I can able to open that using

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your Excel sheets as well.

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See that, automatically your data is arranged in terms of

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rows and columns.

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In terms of rows and columns.

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So guys if you observe while storing your data, right, we

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stored our data by taking comma as the separator between your columns.

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Right. Not only that, you can also store your data by taking

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any other delimiter as well.

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Let's say, I am going to take again same data with a delimiter as

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something like '|' 'serial number', name', suppose 'salary',

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then I am going to take 'skill'.

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Let's say serial number - 1,

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'John', I'm taking salary suppose $2000, 'skill' -

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let's say Python. Same way

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I am going to store one more data.

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You can take anything.

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So here my intention is, in case if we take separator as other

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than comma how you can work with your CSV files, that's important.

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Let me now save this file as some 'new_info.csv'.

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Let me save it as '.csv' file.

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Let's say 'name' as 'new_info.csv'.

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That's it.

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Now previously you stored your data by taking separator as comma,

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but now I have taken separator as pipeline. By default

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if I open that, see that, now you are not getting your data

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in terms of columns.

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See that your Excel sheet is not able to identify your data

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as in terms of columns.

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It has given only one column. But you know the delimiter, right?

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What is the delimiter you used to create your CSV file?

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Just select your column, go to 'Data-> Text to Columns'.

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[no audio]

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delimiter, 'Delimited', right. Just select other, and provide

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your '|' as. See that. Now you're able to fetch your

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data, I mean you are able to convert your data into number

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of columns based on the separator

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you used for your data.

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[no audio]

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So this is also one type of encoding.

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See, if you know pipeline then only you can able to retrieve

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the data from your file.

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So if third person don't know what is the delimiter you

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used for your data, then they can't separate your data.

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Right. So it's like a one type of encoding. Of course, not that much

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good but up to certain limits

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it is good practice.

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That's fine. And guys if you store your data in CSV file, it is very easy

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to transfer your data to your database, or from database to

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if you want to download it is very easy to download into CSV files.

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That's why in real time

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most of the cases you will work with CSV files instead of

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excel sheets.

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[no audio]

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That's fine. Now guys assume that you have one CSV file.

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Now you want to read the data using python. Then how you can read it?

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Right. See let me save a script name called 'read_csv'.

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Anything you can take it. Now,

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I am going to take it,

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I'm going to store somewhere.

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You can store anywhere.

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Let's say I want to store here.

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'read_csv_file.py'. So guys if you want to read a CSV

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file, or if you want to write a data into your CSV file, in

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your python you have a default module called CSV'. First you need to

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import that. This is the default module. You can directly use

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that. Then let me take 'req_file' to read. So suppose that

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file is, suppose

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let's say 'info.csv', right. But guys whenever if you are

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working with files, it is a good practice to provide complete path.

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[no audio]

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Right. See, let me take the complete path for my file.

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So actually it is there in somewhere, right?

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So I'm going to provide complete path for my file.

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And guys you are working with Windows,

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that's why please, please provide '\\' in your path.

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[no audio]

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Yeah, fine. Now you have in your hand your CSV file.

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Next you need to read it.

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So guys forget about the CSV,

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if you want to read a text file, how we can read? Already we

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have seen our previous videos, right?

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Let's say I'm going to open your file in 'read' mode. Your file

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is there in the variable called 'req_file'

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I want to read the content, then open your file in 'read' mode.

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Finally just to close your file.

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Now I want to get the data

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what is there with your CSV file,

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I mean with your file, so 'content' or 'data' equals to simply

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'fo.', I am taking 'readlines'.

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[no audio]

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Then let me print your data.

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So I am going to take one by one line from your 'content'.

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Then, I want to print that. See the result.

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[no audio]

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Yes, you are getting your data line by line.

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Right. So, you know, if you want to remove that space, empty

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line, you can strip it.

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Yes, you are getting. But the thing is this is like a string.

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String means this entire data is like a one column but we

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know CSV is nothing but tabular data.

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So now you are not getting your data as a separate columns.

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Your entire line you're

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getting as a one line only. I should not get like that.

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Because it is a CSV,

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I need to get in terms of columns.

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[no audio]

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Right. Now what you have to do is first you have to read your, you

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have to open your file in 'read' mode, then whatever the data

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you have inside of your file that data

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you need to convert it into

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[no audio]

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rows and columns.

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Anyway you're getting rows, but you need to convert that

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data into columns.

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That's why what you have to do is, you need to parse, you need

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to send your data into CSV,

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so that CSV will convert your data in terms of columns.

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Right. So now see that what I'm doing is 'csv_reader', no need to take

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this much lengthy variable,

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simply you can take, 'csv', 'csv_reader', 'cr', or simply

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'csv', or, 'data', equals to, what you have to do is from CSV module,

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right, use a function called 'reader'.

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So from your file try to convert your rows,

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anyway file is nothing but, normal file is also you're going

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to get line by line. Line is nothing but a row in your CSV.

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But that line consists of, that line consists of columns.

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So CSV will automatically convert your data into columns,

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right. Now see the result.

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[no audio]

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So guys in your data you have all your rows of your CSV in

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terms of columns.

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Let me take, suppose if I directly print your 'data'.

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So that is the object, but inside of that object you have

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number of rows and each row consists of some columns.

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So if you want to see that, 'for each in data', let's say,

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I want to print that. Now see the result.

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What happened?

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'for each in data'.

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[no audio]

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oh, we close that, right? Yeah.

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[no audio]

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Let me close after this.

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[no audio]

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Now see that.

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You are able to get your data.

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See, each line has a list. List means number of values, separate

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values. That means this is one column,

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this is one column, this is

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one column, separate columns you are getting.

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[no audio]

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Right. Separate columns you are getting,

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or in case, in case if you

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don't want to take this, if you don't want to use your CSV,

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right, see what I am doing is let's say I want the content

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of my file, you know 'fo.readlines'. Without CSV module

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also you can convert your data,

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[no audio]

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into number of columns. See that. I am going to print,

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first of all your data line by line. Yes, you are getting.

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But you know, this is the a single row. In this do you have

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four columns. Now,

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if you observe here, this string somewhere you have comma.

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I can split it no,

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simply. Actually this operation is doing by your CSV module.

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That's it. Now see the result. The same data what you are getting from

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your CSV module same thing you can able to get it but no

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need to do this split operation by yourself, that will taken

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care by your CSV module.

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That's why what we are doing is,

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[no audio]

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right, see that.

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[no audio]

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Now 'content' is nothing but from your 'csv' module create a

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'reader' object, or convert your string, string of rows into

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some columns.

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So for that you can do in this way. That's it.

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Now 'for each in content'. Right.

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[no audio]

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Let me 'print(each)'.

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[no audio]

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Now see the result. Yeah, finally

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you need to close your file.

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Don't forget about that.

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'fo.close'.

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[no audio]

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That's it.

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Right. So guys actually CSV is splitting your data based

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on delimiter, but we are not providing anywhere delimiter,

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right. Then how your CSV module is splitting your line into

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a list which consists of your values as columns?

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[no audio]

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We know by default CSV will consider separator as comma.

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CSV is nothing but Comma Separated Values. But in case if

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you want to mention to your CSV, if you want to tell to your

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CSV, "Use this as a separator, delimiter". You can mention, 'delimiter'

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is nothing but ",". That's it. Now see the result.

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[no audio]

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Right. Suppose if I don't mention this, and anyway by default

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your delimiter is comma, by default with your CSV

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that's why CSV will assume that comma is the separator.

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Now we have one more file, right?

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If you observe this file, 'new_info', in that delimiter is not a comma.

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Let me try with that 'new_info'.

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[no audio]

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You're getting your data as one value on your list.

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That means again, you have one column.

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Actually these are four columns in each line, right?

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But you're getting as one column. Then in this case, you

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need a delimiter.

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So for better practice always try to write 'delimiter' as your required thing.

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I mean you just mention your 'delimiter' option as well while

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converting your data into rows and columns.

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That's it.

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Now it is not separated, comma as the separator,

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it has a pipeline as a separator. Now, let me run it.

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What happened? Sorry

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[no audio]

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That's it.

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'delimiter'. So likewise, whatever the delimiter you have in your CSV

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file, if you know that you can able to read your data using

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your Python very easily in this way.

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[no audio]

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Right. Fine.

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So this is the way how we can read your content from your

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CSV file.

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So guys nothing is there.

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Just open your CSV file in 'read' mode like a text file, after

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that you are going to convert your data into tabular data

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by using this operation from CSV '.reader', then provide

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your file object information,

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and what is the delimiter in your CSV file.

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Then you are going to get content. Then in that content

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you have all your rows and columns. Then you need to take

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one by one row.

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See, if it is a CSV file, right, it is having rows. Each row is having

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some columns.

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So all rows if I, I can take by using 'for' loop from your 'content',

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not only 'content', you can take any variable here.

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Right.

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So after reading that then you can close your file.

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[no audio]

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Okay. So guys this is a simple way to read your CSV files.

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While going forward we will

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see different ways to work with your CSV files.

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Okay. In next video

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we'll see how to write a content to your CSV file.

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Okay.

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Okay guys. Thank you for watching this video.

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[no audio]