title
Python Tutorial: CSV Module - How to Read, Parse, and Write CSV Files

description
In this Python Programming Tutorial, we will be learning how to work with csv files using the csv module. We will learn how to read, parse, and write to csv files. CSV stands for "Comma-Separated Values". It is a common format for storing information. Knowing how to read, parse, and write this information to files will open the door to working with a lot of data throughout the world. Let's get started. The code from this video can be found at: https://github.com/CoreyMSchafer/code_snippets/tree/master/Python-CSV ✅ Support My Channel Through Patreon: https://www.patreon.com/coreyms ✅ Become a Channel Member: https://www.youtube.com/channel/UCCezIgC97PvUuR4_gbFUs5g/join ✅ One-Time Contribution Through PayPal: https://goo.gl/649HFY ✅ Cryptocurrency Donations: Bitcoin Wallet - 3MPH8oY2EAgbLVy7RBMinwcBntggi7qeG3 Ethereum Wallet - 0x151649418616068fB46C3598083817101d3bCD33 Litecoin Wallet - MPvEBY5fxGkmPQgocfJbxP6EmTo5UUXMot ✅ Corey's Public Amazon Wishlist http://a.co/inIyro1 ✅ Equipment I Use and Books I Recommend: https://www.amazon.com/shop/coreyschafer ▶️ You Can Find Me On: My Website - http://coreyms.com/ My Second Channel - https://www.youtube.com/c/coreymschafer Facebook - https://www.facebook.com/CoreyMSchafer Twitter - https://twitter.com/CoreyMSchafer Instagram - https://www.instagram.com/coreymschafer/ #Python

detail
{'title': 'Python Tutorial: CSV Module - How to Read, Parse, and Write CSV Files', 'heatmap': [{'end': 306.142, 'start': 237.154, 'weight': 0.773}, {'end': 478.518, 'start': 452.035, 'weight': 0.818}, {'end': 758.365, 'start': 737.439, 'weight': 0.901}, {'end': 847.354, 'start': 821.561, 'weight': 0.799}], 'summary': "Learn how to effectively handle csv files in python, covering file parsing basics, manipulation techniques, and working with csv data, including advantages of using python's csv module and benefits of dictionary reader and writer.", 'chapters': [{'end': 120.575, 'segs': [{'end': 31.143, 'src': 'embed', 'start': 0.249, 'weight': 3, 'content': [{'end': 0.869, 'text': "hey there, how's it going?", 'start': 0.249, 'duration': 0.62}, {'end': 6.011, 'text': "everybody in this video we're going to be looking at how to read, parse and write CSV files.", 'start': 0.869, 'duration': 5.142}, {'end': 10.233, 'text': "now, if you don't know what CSV files are, it stands for comma separated values.", 'start': 6.011, 'duration': 4.222}, {'end': 18.015, 'text': 'basically, CSV files allow us to put into a plain text file some data and use some type of delimiter, usually a comma,', 'start': 10.233, 'duration': 7.782}, {'end': 19.736, 'text': 'to separate the different fields.', 'start': 18.015, 'duration': 1.721}, {'end': 27.1, 'text': 'now I have a sample CSV file here that we can work with and and if we look at this, then we can see how these are usually structured.', 'start': 19.736, 'duration': 7.364}, {'end': 31.143, 'text': "so this can kind of look like a mess, but it's not really meant to be read directly.", 'start': 27.1, 'duration': 4.043}], 'summary': 'Learn how to read, parse, and write csv files, using comma as a delimiter for data separation.', 'duration': 30.894, 'max_score': 0.249, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA249.jpg'}, {'end': 85.05, 'src': 'embed', 'start': 40.25, 'weight': 1, 'content': [{'end': 49.578, 'text': 'now our fields in this file are first name, last name and email, So that tells us the information that we should expect to see on every line.', 'start': 40.25, 'duration': 9.328}, {'end': 57.383, 'text': 'So if I go to the next line here, then we can see that John is the first name and then a comma.', 'start': 49.918, 'duration': 7.465}, {'end': 63.328, 'text': 'Doe is the last name and then a comma and then this long email here is the email.', 'start': 57.383, 'duration': 5.945}, {'end': 66.17, 'text': "So that's why these are called comma separated values.", 'start': 63.728, 'duration': 2.442}, {'end': 69.052, 'text': 'And what separates the values is called a delimiter.', 'start': 66.57, 'duration': 2.482}, {'end': 73.355, 'text': 'So the comma is a common delimiter, but you can use just about anything.', 'start': 69.352, 'duration': 4.003}, {'end': 80.504, 'text': "So sometimes you'll see files with tab delimited values or dashes or things like that, but they're all called CSV files.", 'start': 73.655, 'duration': 6.849}, {'end': 85.05, 'text': "So now let's see what it's like to read, parse, and write to CSV files.", 'start': 80.985, 'duration': 4.065}], 'summary': 'Transcript explains csv file format and its components.', 'duration': 44.8, 'max_score': 40.25, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA40250.jpg'}, {'end': 134.618, 'src': 'embed', 'start': 104.707, 'weight': 0, 'content': [{'end': 110.551, 'text': "So for example, if someone puts a comma or something in their name for some reason, then we wouldn't want to split on that.", 'start': 104.707, 'duration': 5.844}, {'end': 114.334, 'text': 'And also the CSV module will handle new lines and all those things.', 'start': 110.992, 'duration': 3.342}, {'end': 120.575, 'text': 'So it just makes it a lot easier to parse out all the information that we want without writing something complicated from scratch.', 'start': 114.654, 'duration': 5.921}, {'end': 125.796, 'text': "Okay, so to read this CSV file, we're just going to open this file just like any other file.", 'start': 121.015, 'duration': 4.781}, {'end': 134.618, 'text': "So we'll use a context manager here and we'll say with open, and the name of that file that I was just looking at is names.csv,", 'start': 126.116, 'duration': 8.502}], 'summary': 'Csv module simplifies parsing, handling new lines, and avoiding splitting on commas in names.', 'duration': 29.911, 'max_score': 104.707, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA104707.jpg'}], 'start': 0.249, 'title': 'Csv file parsing basics', 'summary': 'Focuses on reading, parsing, and writing csv files, emphasizing the advantages of using the csv module for handling potential complexities effectively.', 'chapters': [{'end': 120.575, 'start': 0.249, 'title': 'Csv file parsing basics', 'summary': 'Explains how to read, parse, and write csv files, defining csv files as comma separated values and highlighting the structure and parsing methods. it also emphasizes the advantage of using the csv module for parsing, handling potential complexities effectively.', 'duration': 120.326, 'highlights': ['The chapter explains how to read, parse, and write CSV files, defining CSV files as comma separated values and highlighting the structure and parsing methods.', 'CSV files allow data to be stored in a plain text file using a delimiter, usually a comma, to separate different fields.', 'The sample CSV file provided in the chapter contains fields for first name, last name, and email, demonstrating the structure and content of CSV files for parsing purposes.', 'The CSV module is recommended for parsing CSV files due to its ability to handle complexities such as commas within data and new lines effectively, making parsing easier compared to writing custom parsing methods.']}], 'duration': 120.326, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA249.jpg', 'highlights': ['The CSV module is recommended for parsing CSV files due to its ability to handle complexities effectively.', 'CSV files allow data to be stored in a plain text file using a delimiter, usually a comma.', 'The sample CSV file provided in the chapter contains fields for first name, last name, and email.', 'The chapter explains how to read, parse, and write CSV files, defining CSV files as comma separated values.']}, {'end': 632.512, 'segs': [{'end': 147.088, 'src': 'embed', 'start': 121.015, 'weight': 0, 'content': [{'end': 125.796, 'text': "Okay, so to read this CSV file, we're just going to open this file just like any other file.", 'start': 121.015, 'duration': 4.781}, {'end': 134.618, 'text': "So we'll use a context manager here and we'll say with open, and the name of that file that I was just looking at is names.csv,", 'start': 126.116, 'duration': 8.502}, {'end': 137.559, 'text': "and it's in the same directory as the file that I'm currently writing.", 'start': 134.618, 'duration': 2.941}, {'end': 140.061, 'text': 'And we want to read this file.', 'start': 138.059, 'duration': 2.002}, {'end': 142.604, 'text': "So we'll put an R there as the second value.", 'start': 140.221, 'duration': 2.383}, {'end': 144.806, 'text': 'And now what we want to call this.', 'start': 143.044, 'duration': 1.762}, {'end': 147.088, 'text': "So we'll say CSV file.", 'start': 144.826, 'duration': 2.262}], 'summary': 'To read the names.csv file, open it using a context manager and read the file in the same directory.', 'duration': 26.073, 'max_score': 121.015, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA121015.jpg'}, {'end': 306.142, 'src': 'heatmap', 'start': 237.154, 'weight': 0.773, 'content': [{'end': 243.937, 'text': "So for example, if we're going by the index, like this would be index 0, then 1, and then the email would be index 2.", 'start': 237.154, 'duration': 6.783}, {'end': 251.059, 'text': "If we only wanted to print out all of the indexes, then on this line here, we could say, let's print out index 2 of each line.", 'start': 243.937, 'duration': 7.122}, {'end': 255.781, 'text': 'And if we run that, then we can see that now we get all of the emails printed out.', 'start': 251.419, 'duration': 4.362}, {'end': 262.403, 'text': "Now if you don't want this first line of the field names and only want the values then we can just skip that first line.", 'start': 256.201, 'duration': 6.202}, {'end': 265.104, 'text': 'So if anyone has seen my video on generators,', 'start': 262.703, 'duration': 2.401}, {'end': 273.327, 'text': 'then we can actually step over values in an iterable by calling next and running next will return the next value if we want to capture that in a variable.', 'start': 265.104, 'duration': 8.223}, {'end': 278.169, 'text': 'But if we just want to step over the value, then we can come up here before our list.', 'start': 273.647, 'duration': 4.522}, {'end': 283.57, 'text': 'We can just say next CSV reader and that will loop over that first line.', 'start': 278.469, 'duration': 5.101}, {'end': 290.873, 'text': 'And then when we iterate through this, it should start at the second value, which is the first person in the list.', 'start': 283.911, 'duration': 6.962}, {'end': 296.455, 'text': 'So now if we rerun this and scroll up to the top, now we can see that that John Doe is now the first value.', 'start': 291.013, 'duration': 5.442}, {'end': 299.277, 'text': "Okay, so now let's see how we can write to a CSV file.", 'start': 296.875, 'duration': 2.402}, {'end': 306.142, 'text': "Now we can do this with any list of values, but since we're already have a list of values here from our original CSV file,", 'start': 299.657, 'duration': 6.485}], 'summary': 'Iterating through csv data, skipping headers, and writing to a csv file.', 'duration': 68.988, 'max_score': 237.154, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA237154.jpg'}, {'end': 290.873, 'src': 'embed', 'start': 265.104, 'weight': 3, 'content': [{'end': 273.327, 'text': 'then we can actually step over values in an iterable by calling next and running next will return the next value if we want to capture that in a variable.', 'start': 265.104, 'duration': 8.223}, {'end': 278.169, 'text': 'But if we just want to step over the value, then we can come up here before our list.', 'start': 273.647, 'duration': 4.522}, {'end': 283.57, 'text': 'We can just say next CSV reader and that will loop over that first line.', 'start': 278.469, 'duration': 5.101}, {'end': 290.873, 'text': 'And then when we iterate through this, it should start at the second value, which is the first person in the list.', 'start': 283.911, 'duration': 6.962}], 'summary': 'Iterate over iterable values using next to capture or skip values.', 'duration': 25.769, 'max_score': 265.104, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA265104.jpg'}, {'end': 348.022, 'src': 'embed', 'start': 321.112, 'weight': 1, 'content': [{'end': 325.374, 'text': "Now first, we're going to want to write the field name headers into the new file.", 'start': 321.112, 'duration': 4.262}, {'end': 329.475, 'text': "So let's take out this next statement where we're skipping over those.", 'start': 325.694, 'duration': 3.781}, {'end': 331.396, 'text': "So now I'll come down here.", 'start': 329.855, 'duration': 1.541}, {'end': 336.978, 'text': "And now actually above our loop, we're going to want to open a new file for writing.", 'start': 331.776, 'duration': 5.202}, {'end': 339.719, 'text': "And so we'll say with open.", 'start': 337.478, 'duration': 2.241}, {'end': 344.12, 'text': "And we'll call this file new underscore names dot csv.", 'start': 340.119, 'duration': 4.001}, {'end': 346.101, 'text': 'We want to open this for writing.', 'start': 344.501, 'duration': 1.6}, {'end': 348.022, 'text': 'So the second argument is a w.', 'start': 346.141, 'duration': 1.881}], 'summary': 'Writing field name headers into new file and opening a new file for writing.', 'duration': 26.91, 'max_score': 321.112, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA321112.jpg'}, {'end': 478.518, 'src': 'heatmap', 'start': 452.035, 'weight': 0.818, 'content': [{'end': 461.56, 'text': 'And then for each line in this original CSV data, we are writing out to the new file each line of the original file.', 'start': 452.035, 'duration': 9.525}, {'end': 467.266, 'text': "So now, if we run this, then we don't have any output here at the bottom.", 'start': 461.98, 'duration': 5.286}, {'end': 472.912, 'text': "but it should have created this new file called newnames.csv, and I'll go ahead and open that up.", 'start': 467.266, 'duration': 5.646}, {'end': 478.518, 'text': "Now we can see in this new file that it's using dashes instead of commas for the delimiter.", 'start': 473.352, 'duration': 5.166}], 'summary': 'Original csv data is written to new file with dashes as delimiter.', 'duration': 26.483, 'max_score': 452.035, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA452035.jpg'}, {'end': 539.493, 'src': 'embed', 'start': 514.192, 'weight': 2, 'content': [{'end': 522.222, 'text': 'the CSV writer knew to put quotes around the last name so that it can tell the difference between the delimiters and the values that just happen to contain dashes.', 'start': 514.192, 'duration': 8.03}, {'end': 528.967, 'text': "So now that we've seen how that works, let's actually change this delimiter for the new file to something that's a bit more common.", 'start': 522.722, 'duration': 6.245}, {'end': 533.67, 'text': 'So aside from commas, tabs are very common delimiters.', 'start': 529.267, 'duration': 4.403}, {'end': 535.291, 'text': "So let's use tabs instead.", 'start': 533.79, 'duration': 1.501}, {'end': 539.493, 'text': 'And in Python, a tab can be represented with this backslash T.', 'start': 535.611, 'duration': 3.882}], 'summary': 'Using tabs as delimiters improves csv handling in python.', 'duration': 25.301, 'max_score': 514.192, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA514192.jpg'}, {'end': 632.512, 'src': 'embed', 'start': 605.902, 'weight': 5, 'content': [{'end': 614.305, 'text': "So we can see that each line only has one value and it didn't split on the values on the tab because it was expecting commas.", 'start': 605.902, 'duration': 8.403}, {'end': 619.987, 'text': 'So instead you have to explicitly pass in that we want the delimiter to be a tab.', 'start': 614.585, 'duration': 5.402}, {'end': 629.471, 'text': "So I'll pass that into the reader method here and say delimiter equals a backslash slash T for tab and then rerun that.", 'start': 620.287, 'duration': 9.184}, {'end': 632.512, 'text': 'And now you can see that we get the correct parsing.', 'start': 629.831, 'duration': 2.681}], 'summary': 'Using tab as delimiter, the correct parsing is achieved.', 'duration': 26.61, 'max_score': 605.902, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA605902.jpg'}], 'start': 121.015, 'title': 'Csv file manipulation in python', 'summary': "Covers reading and writing csv files in python, including opening a csv file, reading its content, skipping the header, iterating through the content, and writing to a new csv file with a different delimiter. it also explains how to use python's csv module to manipulate csv files, change delimiters, and specify delimiters when reading tab-delimited files.", 'chapters': [{'end': 388.505, 'start': 121.015, 'title': 'Reading and writing csv files in python', 'summary': 'Discusses reading and writing csv files in python, covering topics such as opening a csv file, reading its content, skipping the header, iterating through the content, and writing to a new csv file with a different delimiter.', 'duration': 267.49, 'highlights': ['Opening a CSV file using a context manager and reading its content using a CSV reader, iterating through the lines, and understanding the structure of the data.', 'Writing to a new CSV file with a different delimiter and handling the field name headers.', 'Skipping the first line of the CSV file, using next to step over values in an iterable, and understanding the impact of using a different delimiter when writing to a new CSV file.']}, {'end': 632.512, 'start': 388.945, 'title': 'Csv file manipulation in python', 'summary': "Explains how to use python's csv module to read and write csv files, including changing delimiters, with examples of using dashes and tabs, and the need to specify the delimiter when reading a tab-delimited file.", 'duration': 243.567, 'highlights': ['The CSV writer is used to write the original CSV file into a new file with a specified delimiter, such as a dash or a tab, demonstrating the ability to handle special characters like hyphens and tabs within the data.', 'The process of changing the delimiter to a more common one, such as tabs, is explained, and the resulting tab-delimited file is shown to be more readable than the original.', 'The importance of specifying the delimiter when reading a tab-delimited file is highlighted, as failing to do so results in incorrect parsing of the data.']}], 'duration': 511.497, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA121015.jpg', 'highlights': ['Opening a CSV file using a context manager and reading its content using a CSV reader, iterating through the lines, and understanding the structure of the data.', 'Writing to a new CSV file with a different delimiter and handling the field name headers.', 'The CSV writer is used to write the original CSV file into a new file with a specified delimiter, such as a dash or a tab, demonstrating the ability to handle special characters like hyphens and tabs within the data.', 'Skipping the first line of the CSV file, using next to step over values in an iterable, and understanding the impact of using a different delimiter when writing to a new CSV file.', 'The process of changing the delimiter to a more common one, such as tabs, is explained, and the resulting tab-delimited file is shown to be more readable than the original.', 'The importance of specifying the delimiter when reading a tab-delimited file is highlighted, as failing to do so results in incorrect parsing of the data.']}, {'end': 958.85, 'segs': [{'end': 674.844, 'src': 'embed', 'start': 651.397, 'weight': 0, 'content': [{'end': 658.159, 'text': 'But my preferred method is working with CSV data using the dictionary reader and the dictionary writer.', 'start': 651.397, 'duration': 6.762}, {'end': 662.74, 'text': "So let's take a look at those and I'll explain why I prefer them over the regular reader and writer.", 'start': 658.479, 'duration': 4.261}, {'end': 665.921, 'text': "Okay, so first let's take a look at the dictionary reader.", 'start': 662.76, 'duration': 3.161}, {'end': 671.883, 'text': "So to use this, we're just going to replace the regular reader method here with a dict reader.", 'start': 666.301, 'duration': 5.582}, {'end': 674.844, 'text': "And now let's print out the lines that we get with this.", 'start': 672.563, 'duration': 2.281}], 'summary': 'Prefer using csv dictionary reader and writer over regular methods.', 'duration': 23.447, 'max_score': 651.397, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA651397.jpg'}, {'end': 727.397, 'src': 'embed', 'start': 696.662, 'weight': 1, 'content': [{'end': 699.305, 'text': 'It starts off immediately with the first person.', 'start': 696.662, 'duration': 2.643}, {'end': 705.09, 'text': 'So the reason is that the field names are now the keys of each of these values here.', 'start': 699.625, 'duration': 5.465}, {'end': 709.831, 'text': 'Now the reason that I like this is because it makes it a lot easier to parse out the information that we want.', 'start': 705.49, 'duration': 4.341}, {'end': 713.192, 'text': 'So, for example, remember when we used the regular reader?', 'start': 710.172, 'duration': 3.02}, {'end': 718.494, 'text': 'If we wanted to print out the email address, then we printed out the second index of our line.', 'start': 713.873, 'duration': 4.621}, {'end': 723.276, 'text': "Well, for anyone reading your code, it isn't obvious what that second index is.", 'start': 718.854, 'duration': 4.422}, {'end': 727.397, 'text': "So they'd have to go into the CSV file to find that information out.", 'start': 723.576, 'duration': 3.821}], 'summary': 'Using field names as keys makes parsing information easier and improves code readability.', 'duration': 30.735, 'max_score': 696.662, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA696662.jpg'}, {'end': 770.375, 'src': 'heatmap', 'start': 737.439, 'weight': 0.901, 'content': [{'end': 739.039, 'text': 'So we just access that key.', 'start': 737.439, 'duration': 1.6}, {'end': 743.26, 'text': 'So now if we rerun that, then we can see that now we have all of the email information.', 'start': 739.359, 'duration': 3.901}, {'end': 746.621, 'text': "Okay, and now let's look at how to use the dictionary writer.", 'start': 743.7, 'duration': 2.921}, {'end': 753.602, 'text': "So I'm going to remove this loop and then uncomment out the rest of this information here.", 'start': 747.001, 'duration': 6.601}, {'end': 758.365, 'text': "Now with the dictionary reader we really didn't need to change anything,", 'start': 754.742, 'duration': 3.623}, {'end': 763.069, 'text': 'but with the dictionary writer we actually have to provide the field names of our file.', 'start': 758.365, 'duration': 4.704}, {'end': 770.375, 'text': "So one line above our writer here I'm just going to create a list of the field names.", 'start': 763.429, 'duration': 6.946}], 'summary': 'Access key, retrieve email information, utilize dictionary writer and reader.', 'duration': 32.936, 'max_score': 737.439, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA737439.jpg'}, {'end': 821.221, 'src': 'embed', 'start': 791.934, 'weight': 3, 'content': [{'end': 795.976, 'text': "So I'll say field names is equal to field names.", 'start': 791.934, 'duration': 4.042}, {'end': 799.64, 'text': "Okay, and now we're ready to write the data.", 'start': 797.097, 'duration': 2.543}, {'end': 807.388, 'text': 'So with the dictionary writer, you have the option of whether or not you want to write out those headers, which are the field names in the first row.', 'start': 800.02, 'duration': 7.368}, {'end': 817.079, 'text': 'So if we want those headers, which most of the time I do, then we can say CSV writer dot write header.', 'start': 807.729, 'duration': 9.35}, {'end': 821.221, 'text': "So that's going to write out those field names as the first line.", 'start': 818.499, 'duration': 2.722}], 'summary': 'Using csv writer to write field names as headers in the first row.', 'duration': 29.287, 'max_score': 791.934, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA791934.jpg'}, {'end': 865.34, 'src': 'heatmap', 'start': 821.561, 'weight': 2, 'content': [{'end': 831.126, 'text': 'And once the header is written out, we can loop through the lines of the original file, just like we did before, and say csvwriter.WriteRow,', 'start': 821.561, 'duration': 9.565}, {'end': 832.467, 'text': 'and then pass in that line.', 'start': 831.126, 'duration': 1.341}, {'end': 833.808, 'text': 'So all of that stays the same.', 'start': 832.487, 'duration': 1.321}, {'end': 840.932, 'text': 'So if we run this and then look over here at our new names CSV file, then we can see that that still worked.', 'start': 834.188, 'duration': 6.744}, {'end': 847.354, 'text': "And like I said before, the reason that I like working with the dictionary reader and writer is because it's more obvious what you're doing.", 'start': 841.892, 'duration': 5.462}, {'end': 855.057, 'text': "So let's say, for example, that in our new CSV file, we actually only wanted the first and last names and wanted to leave off the email.", 'start': 847.674, 'duration': 7.383}, {'end': 859.698, 'text': "Well, with the regular reader and writer, we'd be modifying the indexes of those lists.", 'start': 855.457, 'duration': 4.241}, {'end': 865.34, 'text': "And like I mentioned before, it's not obvious by looking at an index what value it's supposed to hold.", 'start': 860.078, 'duration': 5.262}], 'summary': 'Demonstrates using csvwriter to manipulate csv files and explains the benefits of working with dictionary reader and writer.', 'duration': 43.779, 'max_score': 821.561, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA821561.jpg'}, {'end': 958.85, 'src': 'embed', 'start': 944.516, 'weight': 4, 'content': [{'end': 946.998, 'text': 'The easiest way is to simply like the video and give it a thumbs up.', 'start': 944.516, 'duration': 2.482}, {'end': 950.761, 'text': "And also it's a huge help to share these videos with anyone who you think would find them useful.", 'start': 947.318, 'duration': 3.443}, {'end': 955.886, 'text': "And if you have the means, you can contribute through Patreon and there's a link to that page in the description section below.", 'start': 951.261, 'duration': 4.625}, {'end': 958.85, 'text': 'Be sure to subscribe for future videos and thank you all for watching.', 'start': 956.287, 'duration': 2.563}], 'summary': 'Encourage likes and shares, and patreon contributions for support.', 'duration': 14.334, 'max_score': 944.516, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA944516.jpg'}], 'start': 632.972, 'title': 'Working with csv data in python', 'summary': 'Compares regular reader and writer with dictionary reader and writer in python for working with csv data, emphasizing the benefits of the latter for easier parsing. it also provides examples of accessing and modifying data fields and options for writing headers and selectively writing data.', 'chapters': [{'end': 713.192, 'start': 632.972, 'title': 'Working with csv data in python', 'summary': 'Explains the differences between using the regular reader and writer and the dictionary reader and writer when working with csv data in python, highlighting the benefits of the latter method for easier parsing of information.', 'duration': 80.22, 'highlights': ['The dictionary reader and writer is the preferred method for working with CSV data in Python, as it makes it easier to parse out the information that we want.', 'Using the dictionary reader, each value becomes an ordered dictionary with field names as keys, simplifying the parsing process.']}, {'end': 958.85, 'start': 713.873, 'title': 'Working with csv files in python', 'summary': 'Discusses how to use dictionary reader and writer to read, parse, and write csv files, making it more obvious and easier to manipulate data. it provides examples of accessing and modifying data fields, and demonstrates options for writing headers and selectively writing data. the tutorial also encourages support through likes, shares, and patreon contributions.', 'duration': 244.977, 'highlights': ['The chapter explains how to use dictionary reader and writer to make it more obvious and easier to manipulate data, providing examples of accessing and modifying data fields. It demonstrates options for writing headers and selectively writing data.', 'The tutorial encourages support through likes, shares, and Patreon contributions, providing various ways for the audience to support the content.']}], 'duration': 325.878, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/q5uM4VKywbA/pics/q5uM4VKywbA632972.jpg', 'highlights': ['The dictionary reader and writer is the preferred method for working with CSV data in Python, as it makes it easier to parse out the information that we want.', 'Using the dictionary reader, each value becomes an ordered dictionary with field names as keys, simplifying the parsing process.', 'The chapter explains how to use dictionary reader and writer to make it more obvious and easier to manipulate data, providing examples of accessing and modifying data fields.', 'It demonstrates options for writing headers and selectively writing data.', 'The tutorial encourages support through likes, shares, and Patreon contributions, providing various ways for the audience to support the content.']}], 'highlights': ['The dictionary reader and writer is the preferred method for working with CSV data in Python, as it makes it easier to parse out the information that we want.', 'The CSV module is recommended for parsing CSV files due to its ability to handle complexities effectively.', 'Opening a CSV file using a context manager and reading its content using a CSV reader, iterating through the lines, and understanding the structure of the data.', 'Using the dictionary reader, each value becomes an ordered dictionary with field names as keys, simplifying the parsing process.', 'Writing to a new CSV file with a different delimiter and handling the field name headers.', 'The sample CSV file provided in the chapter contains fields for first name, last name, and email.']}