How do I rename columns in a pandas DataFrame?

You will often want to rename the columns of a DataFrame so that their names are descriptive, easy to type, and don't contain any spaces. In this video, I'll demonstrate three different strategies for renaming columns so that you can choose the best strategy to fit your particular situation.
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== RESOURCES ==
GitHub repository for the series: github.com/jus...
"rename" documentation: pandas.pydata.o...
"read_csv" documentation: pandas.pydata.o...
"str.replace" documentation: pandas.pydata.o...
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[@dataschool]

Starting in pandas version 0.21 (released October 2017), you can rename columns using a "mapper" along with the "axis", similar to how you specify which columns you want to drop. Learn more in my latest video, "5 new changes in pandas you need to know about": kzbin.info/www/bejne/qpaYe6WJeLxggrs

[@NitinSaseendran]

Thanks for your amazing videos. It helped me a lot.

[@dataschool]

You're very welcome!

[@IncredibleGrim]

2:05 why are names like u'City' instead of just 'City'?

[@xyxyirish]

You are a good, kind man. One day people are going to write poems about you.

[@dataschool]

HA! Thank you :)

[@Elias-ce3ze]

Hello, I am from Brazil and I'm usually write my codes in Fortran and Matlab. However I've decided to learn python. Your channel is amazing, it is clear and easy to understand and straight to the goal. Congratulations !!!!

[@dataschool]

Awesome! Thanks so much for your kind words!

[@felipecaannavarro5441]

Opa conterrâneo (=-) Estou começando a aprender programação e estou muito ansioso para fazer aqueles projetos massa com pandas e matplotlib 00 TAMU JUNTO!! BORA FICAR RICO!! kkk

[@fet1612]

I found the Data School's videos to be super helpful for beginners or absolute beginners alike. One thing every learner needs to do is PRACTICE ALONG as Kevin of Data School walks them through each ITEM of EACH video. PAUSE and PRACTICE, PAUSE and PRACTICE, PAUSE and PRACTICE. This way you will be surprised how fast this PAUSE and PRACTICE exercise elevates your rate of understanding. I experimented with the THEMATICS employing this PEDAGOGY, and it worked WONDERS. Data School short videos are most helpful and my most favorite. In an hour-long video, your study material might GET BURIED in HEAPs. But here, you can easily LOCATE your MATERIAL. Good luck with anyone learning at DATA SCHOOL, and BECOME DATA SCIENTISTS of the FUTURE.

[@dataschool]

Thanks so much for your kind words!

[@nikhilkorra5712]

During this Quarantine, thought to gain a new skill but fortunately, I got the best tutor. Thank you, Sir.

[@mokhadra9289]

That bonus worth the whole 9 minutes :) you are ROCK ... thank you :D

[@dataschool]

Awesome! You're welcome!

[@yucelozyazgan]

Simply, he is a great tutor !

[@dataschool]

Thanks!

[@travelogue.brothers]

how everything you teach gets stored in the brain library. can import what you have taught anytime. I am a begineeer to data science and the way you teach topi by topic it is so smooth and satisfying to learn. Thanks a lot

[@dataschool]

Thanks very much for your kind words!

[@СтепанЦыбин-ю9д]

Great teacher. I could not find an explanation for all this nuance in my own language. And here is a gift. Thank you so much, I am waiting for any of your lessons on the channel.

[@dataschool]

Thank you so much! Have you seen my latest pandas tutorial? kzbin.info/www/bejne/moHafZ-AoLh7gtE

[@ramlabasharat4334]

best tutorials on youtube... your all videos are really informative and easy to understand. I'm watching continuously but didn't get bored. your way of teaching is really awesome

[@dataschool]

Thanks so much, I really appreciate it! :)

[@AlexanderMoen]

Thank you, man. I've been searching forever for this seemingly simple thing, and minute 1-3 did it for me. Thanks again.

[@dataschool]

Awesome!

[@nilewilliams9613]

Incredible tutor, definitely going to watch the entire series.

[@dataschool]

Great to hear!

[@shankeybharadwaj1561]

Awesome video lectures... For the bonus tip , I used ufo.columns = list(map(lambda s:s.replace(' ','_') , ufo.columns))

[@fet1612]

DataSchool: Kevin Markham 05:29 Renaming columns in a DataFrame: Kevin: You can actually RENAME the COLUMN while you're reading in the file. Now when I'm reading in the file, here is what I can do to OVERWRITE the COLUMN NAMES. 06:01

[@pranitgandhi6832]

Where were you?? If I had found you earlier my job would have been so easy. Nevertheless, you have done a world of good to me. Thanks a lot for saving my time on reading this stuff from books.

[@dataschool]

That's so kind of you to say! I really appreciate it 😊

[@anantgupta305]

Bro u are simply awesome, you dont know how much of my time u saved and made everything so simple

[@mohamedel-gazzar5818]

This dude is the man. You have helped me soooo much you have no idea!

[@dataschool]

🙌

[@mahnoorafridi9872]

Best tutor I ever had ,you did a great job

[@dataschool]

Wow, thanks!

[@bhavyakothari635]

Simple and easy to understand. You are the best !!! :))

[@dataschool]

Thanks so much! :)

[@syedramishhussain5362]

short and to the point, was v helpful! Thank you

[@satyamagrawal1191]

Your bonus tips are awesome!

[@dataschool]

Thanks!

[@tanned_cosines_]

helped a lot, this playlist; you've provided multiple ways to do a single task thanks a lot

[@dataschool]

Glad it was helpful!

[@airevancarmen]

very simple and complete overview of methods!

[@dataschool]

Thanks!

[@s.baskaravishnu22]

I very much congratulate you for sharing code used in video with us. Many thanks for that. It is very much useful to me. My warm regards to you.

[@dataschool]

Glad to hear that it is useful to you! All of the code from this video series can be found in the following notebook: nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/pandas.ipynb

[@nataliaagudelo8635]

All of your videos are amazing, thank you again!

[@dataschool]

Thanks!

[@sdoken]

Thanks for the cool trick at 8:06 A question about this tip: How could we have known (without you telling us here) that we can call .str. method on ufo.columns here? >>> type(ufo.columns) returns pandas.core.indexes.base.Index object. You showed in another video that we can call .str. on pandas dataframes and linked us to pandas api which shows this under string handling. But I did not know you could run .str. method on ufo.columns because ufo.columns is not a dataframe object. I will appreciate your help!

[@dataschool]

I think I just figured out that string methods works on the columns attribute by trying it! I'm not sure if it's explicitly documented.

[@mohitseventeen]

How can we use the way explained at 4:40 but in method chaining way.

[@lukerengel8533]

When you renamed the columns to all be lower case by first creating a list and then assigning that list to your df.columns object you could also use your tip at the end to do df.columns = df.columns.str.lower() to get the same result in one line of code.

[@dataschool]

Great suggestion, thank you!

[@superfed2742]

i have data which has date format as 20170710 and time(in another column) as 115900(11:59:00) and i want to change the format to be 2017-07-10 11:59:00 in the same column. Because this is pandas format if i understand correctly. How to do like i said?

[@dataschool]

I think you would need to combine those two columns into the same column, and then define the format when using the 'to_datetime' function. See here for details: pandas.pydata.org/pandas-docs/stable/generated/pandas.to_datetime.html Hope that helps!

[@maikeruschannel9002]

Great video. Really helpful for beginners

[@dataschool]

Thank you!

[@TR3NDSETR]

Fabulous, and on to the next.

[@dataschool]

Thank you!

[@rainfrog4116]

Another great video! Thank you, Kevin!

[@dataschool]

You're very welcome! Thanks for your comment.

[@DennisAllard]

There are several ways to run Python in a command line REPL (read eval print loop). NOT all of them have the pretty format shown in these videos. And some have annoying screen width limitations and different behavior for TAB, ,shift-TAB, etc. To see the exact same GUI being used in in these videos I use: Anaconda Navigator > Jupyter > New > Notebook: Python3

[@dataschool]

Thanks for sharing!

[@void2258]

I was typing out your bonus question to ask it just as you got to it.

[@dataschool]

+Elliot Jenner Ha! Great :)

[@joescanlon7502]

ha - i had the exact same query!

[@samiagharib3796]

Thanks for the tutorial especially the bonus tip .

[@dataschool]

Glad it was helpful!

[@jaquesderasmo5496]

You are the best man. Thank you

[@dataschool]

Thank you!

[@jordiblanco5223]

Many thanks for the tutorials. Great job!

[@dataschool]

You're very welcome!

[@irinaelisova1618]

Thank you so much! Bonus tip was quite useful!

[@dataschool]

You're very welcome!

[@leojames22]

This is very useful video. Thanks for sharing. Well explained as well.

[@dataschool]

You're welcome!

[@riteshsingh118]

Love your work ❤️❤️❤️

[@dataschool]

Thank you!

[@akira_asahi]

Thank you for the video. I am grateful for your time and contribution. Kind regards, Akira.

[@dataschool]

You're welcome!

[@salayhin]

Following line will lowercase the column name and replace space with underscore: ufo.columns = ufo.columns.str.lower().str.replace(' ', '_')

[@dataschool]

Indeed it will! The chaining together of multiple string methods is often useful.

[@annayakovleva6983]

Thank you for this! I was just wondering how to save the newly formatted column names to the df!

[@rajarshichowdhury8617]

I have a question whether you can suggest for a python and R course of data science

[@robindong3802]

Very detailed lesson. thank you!

[@dataschool]

You're welcome!

[@goldensleeves]

Why do your column names get that "u" next to them????? Like at 8:34 . Thanks!

[@ChartExplorers]

The "u" in front of the string values indicates that it is a Unicode string instead of ASCII. This will happen when using Python 2. Python 3 strings are Unicode by default so you will not see this.

[@dataschool]

Exactly!

[@jongcheulkim7284]

Thank you so much. This is very helpful.

[@dataschool]

Great to hear! 🙏

[@AshishSahu25]

Thanks for the lucid explanation and bonus tips. I'm wondering using your last bonus tip code snippet, how would I replace or rename few columns' white spaces with underscore, without applying it on all.

[@dataschool]

Glad you liked the video! Regarding your question, my methodology would depend on the exact circumstances. There's not one obvious way to do what you are describing... sorry!

[@ScholarStream_25]

Brilliant 😉🔥. But can anyone tell me how did he get the URL from??

[@lucasmoraes5488]

From his GitHub repository. If you click on raw in some file you'll be redirected to a page

[@cutedevil069]

Best Tutorial ever

[@dataschool]

Thanks!

[@isaiaspereira2796]

Dude, you are awesome!!!

[@dataschool]

Thank you!

[@jingchu4629]

Thanks for the awesome tutorial!

[@dataschool]

You're welcome!

[@ankhts]

Thank you for all the videos.It provides almost all fundamental operations that can be done on Data frames. What understood from this video is that df.columns is used as series along the row 0.Can we do similar thing along column 0 (i.e. index column ) and apply similar operations ? Many thanks

[@szamoransky]

Does str.replace also have an inplace argument?

[@yandongbi1800]

Very grateful for your perfect contribution. I want to ask you what "header = 0" means.Look forward to your reply.

[@dataschool]

header=0 means that the first row (row zero) is contains the header information.

[@assafcohen3173]

I was looking for a way to easily replace column names using regex and got lost in an endless stack overflow loop - thanks for providing an easy solution.

[@dataschool]

You're welcome!

[@ramakanthrayanchi8888]

Excellent video. Cheers :) :)

[@dataschool]

Thanks! :)

[@sdoken]

If I have column labels that are of time datetime, and I want to convert them to strings, how can I do that? Without using a loop. (I already figured out how to do it with a loop by using the rename function at each iteration) Thanks!

[@dataschool]

This should work: df.column_name.astype(str)

[@IBRAHIMDEMIREZ]

Hi Kevin! Your videos are really helpful and very informative, my question is how am i suppose to rename column name on the base of condition? I mean df.columns = df.iloc[16] . row 16 has some NaN values so only for these case I want pd take value from row 17. Thank you!

[@phuccoiinkorea3341]

Easy to a person bad English like me! Thank so much!

[@dataschool]

You're very welcome!

[@chd9841]

some of my variables have spaces and some have dots. I want to replace the spaces dots by underscore how can I do that in one code?

[@dataschool]

You could chain two str.replace operations together in the same line.

[@alexandermuir8160]

Excellent information provided. Qn: Can you use more than one DataFrame simultaneously? If so what is the protocol so the program does not confused as to which one it is using?

[@dataschool]

You reference DataFrames by name, that's all. Glad you liked the video!

[@gokulkannan788]

How do we make our DataFrame or table representation in our jupyter notebook look like yours - with borders? :) We get tables without any borders only.

[@ChartExplorers]

Sometimes when you use print() the table will not have borders. You can also put this into any cell and you should get borders. %%HTML table.dataframe td, table.dataframe th { border: 1px black solid !important; color: black !important; }

[@sameeral-janabi5966]

Thank you .... excellent information.

[@rhettsmedia]

Hi there this is the right place to do this when you paste in a line from your snippets please read the entire line character by character if possible for those of us with visual impairment we do not look at the screen but we must hear all the characters the same as with your URL secure paste in it was very hard to find that this was the I T.LY because we can’t really see the tail the Y from the eye thank you

[@juanmoctezuma9225]

awesome tutorial thanks!

[@terrancedejesus625]

Great video! I would like to know how I can look for certain values in each row or column and then replace those values with a specific value. An example would be, for each cell in a dataframe where the Shape Reported is TRIANGLE and the State is NY, change the cell value in the City column to Buffalo. I hope that makes sense. Thank you!

[@dataschool]

You can definitely do that. Try watching these two videos (in order), and see if you are able to figure out: kzbin.info/www/bejne/rqfTf3Rtl6hrmdU kzbin.info/www/bejne/aoOXiKZ6f5J-jMU Let me know if that helps! :)

[@keerthiallam830]

Thanks for the video! While replacing the column names with .rename method, I am getting 'TypeError: 'set' object is not callable'. Could you please explain this?

[@dataschool]

I'm pretty sure you have a typo... could you check that you are typing the code exactly the same way?

[@nitishrele007]

Why the name of the columns are of the form u'var_name'? (Name of the columns are preceded by the letter u and enclosed in a quote)

[@dataschool]

Python 2 puts a u in front of Unicode strings, whereas Python 3 does not.

[@sdoken]

Is that .str() method at the end of the video (bonus tip) a method of pandas Series or is it a method of string type in python? I am just curious about this. Thanks for the video.

[@dataschool]

You're welcome! 'str' is a namespace where pandas string methods are stored, and 'replace' is a Series method. It's designed to work similar to a Python string method, but it is actually implemented in pandas code. More information about string methods is here: kzbin.info/www/bejne/mKDJknZmfsieftE Hope that helps!

[@vivektiwari3459]

Can we create a transition table and use the translate method instead of replace?

[@dataschool]

I've never used the translate method in pandas, but it looks like translate is for character-by-character translation, so it wouldn't be appropriate in this case.

[@vivektiwari3459]

I tried using translate method on a data set to replace ' ' with '_' and '-' with '_' and it worked in a single line of code. Though you are right it would not be appropriate in this case and not likely to be of significant use in any other case, I guess. Thanks for the video series.

[@dataschool]

You're welcome!

[@merumomo]

Hi! I got a question. How do you undo the changes? How do you change the column names back to what they were before.

[@dataschool]

If you use the "inplace=True" parameter, the changes are permanent, and there is no undo. If you use "inplace=False" (the default), then the change is only temporary. I have a video about inplace coming out on Tuesday!

[@merumomo]

+Data School ok. cool. thank you!

[@IncredibleGrim]

2:05 why are names like u'City' instead of just 'City'

[@dataschool]

It stands for 'u', meaning a Unicode string. That's how Unicode strings were displayed in Python 2.

[@vaibhavdesai6998]

How do we change data types of multiple columns from object to integer in a pandas dataframe? Do you have a video on this? If not could you please make one. That would be really helpful.

[@dataschool]

Great question! This video includes the answer: kzbin.info/www/bejne/Y3_Fimp7bs1-rs0m45s

[@liaqatali1415]

hello can you kindly help me, whatever text editor i use as pycharm, anaconda.. it doesn't shows full table.. it only shows first and last column and other in centers shows in dots.. i am looking in your videos you are getting a proper table.. i dont get full table

[@liaqatali1415]

its shows like this City Colors Reported ... State Time 0 Ithaca NaN ... NY 6/1/1930 22:00 1 Willingboro NaN ... NJ 6/30/1930 20:00 2 Holyoke NaN ... CO 2/15/1931 14:00 3 Abilene NaN ... KS 6/1/1931 13:00 4 New York Worlds Fair NaN ... NY 4/18/1933 19:00

[@dataschool]

This video might be helpful to you: kzbin.info/www/bejne/a5C0iYCtmt-DgKc

[@swagatmishra9350]

hey..what is the difference btw header= None(as stated by you in the previous v d o) and header=0?

[@dataschool]

I believe header=None means "there is no header" and header=0 means "the first row is the header", but I'd have to look it up to be sure.

[@hightimeframe]

super, clear and helpful

[@dataschool]

Great! Thanks for your kind words.

[@AsifMarazi]

Hello... I created a dataframe (Particular month data) from a CSV file I want to add column names or labels. Can I do that...Or I have to write a separate CSV file then add the column names in excel and come back to python...Thats what I am doing right now....Any kind of help will be highly appreciated....I am a absolute beginner....

[@dataschool]

You can just overwrite the columns attribute with the list of column names: df.columns = ['col1', 'col2', 'col3'] Does that help?

[@subashkattel7033]

Kevin, you are doing great job with nice tutorials. Thanks. I have a question, how can we assign name to the series rather than renaming? Say I have 100 columns in a csv file with common index and header are empty(no names). Now I want to assign name to each column like P1, P2, ......P100. Can I do that?

[@dataschool]

The columns attribute of a DataFrame always has values, it is never empty. If you want to change those values, you could use a string method. Hope that helps!

[@varunupadhyay3836]

Hi Kevin, Does header=0 and header=None means the same as they both are producing the same results?

[@dataschool]

Actually, header=0 means that row 0 of the file is the header row, whereas header=None means that there is no header row in the file. Does that help?

[@varunupadhyay3836]

Yes. Sorts things out. Thanks

[@dishonfano7599]

Great job man...

[@dataschool]

Thanks!

[@dharmendra811]

nice to have these videos, helping me alot...would you please make on video to add existing dataframe to predefined worksheet.

[@dataschool]

Do you mean an Excel worksheet?

[@dharmendra811]

Yes.

[@dataschool]

Great, thanks for the suggestion!

[@valeriapir1268]

Your tutorials are just great! Thank you for that!! One question: Is it possible to change the cells depending on its content? I mean, if we see "ABC12" in cell that should be renamed with "Sample"? Thank you in advance! :)

[@dataschool]

You could use the map or replace methods to do that, I think!

[@valeriapir1268]

Thanks to your tutorials i start my journey with Python language!

[@govindrao6479]

hi, am a beginer in Padas. Why does your output of ufo.columns has prefix by 'u' whereas when I tried there is no prefix

[@ChartExplorers]

The "u" in front of the string values indicates that it is a Unicode string instead of ASCII. This will happen when using Python 2. Python 3 strings are Unicode by default so you will not see this.

[@dataschool]

Exactly!

[@abhilash8492]

type(ufo_cols) is list whereas type(ufo.columns) is pandas.core.indexes.numeric.Int64Index. How come we can equate them?what does int64index mean?

[@dataschool]

ufo_cols is a Python list, whereas ufo.columns is a list-like object called an index. They are just different data structures - list comes from Python, whereas index comes from pandas. I recommend watching this video to learn more about the index: kzbin.info/www/bejne/hYq9f55tj56mbKs

[@ish694]

Hey man ! Loving this series. Just one question. How do you remember all these commands and functions and where to put where ? i am new to coding and so i keep forgetting what the commands were. :/

[@dataschool]

I hear you! It's easy to forget when you are getting started. I just remember them more and more over time! Plus, I make cheat sheets for myself like this: nbviewer.jupyter.org/github/justmarkham/pandas-videos/blob/master/pandas.ipynb

[@ish694]

Thanks a lot :D I think these will do the work

[@Mufasa1482]

your first method for renaming columns was "df.rename.columns=". when you used "ufo.rename" you included the argument "inplace=True" to make the change permanent. however, you also presented some other methods for doing the same thing, like defining a list and then applying it by "ufo.columns=list" but this time you did not need to specify "inplace=True". why not?

[@dataschool]

Great question! When you are overwriting an attribute, that will always be immediate and permanent. But when using a method such as rename, that will only be permanent when you use the inplace parameter. Does that help?

[@davidlang32]

How would you suggest dynamically rename column headers while looping through multiple files? The files are server resource data for CPU. There's over 100 servers which are being read into a Data Frame, one at a time. The script merges data based on the time stamp and only adds the average and 95 percentile of each file to a new Data Frame. That data frame continues to get updated with each file until it has all the average and 95th percentile data from all files. This issue is that since each file has the same format the columns names are all the same. This doesn't differentiate from each of the servers. Through the process of merging the data into one master file I lose the ability to see which column belongs to which file. How would you tackle this issue?My current method: I used your method in this video to rename all the columns prior to completing the final save. It just writes all the file names as they should appear. The data is very structured so this works. However, this would not work in an environment where the data naming patterns were not as structured. Thanks for any insight you maybe able to provide.

[@dataschool]

Great question! There's no obvious answer here, so I'd have to see more of the specifics to advise. Sorry I can't help!

[@salq6585]

How to create data structure for my dataset? Note : I opened the data in the same way you did it but I want to help creating the data structure like dictionary. Thanks

[@dataschool]

I'm sorry, I don't understand your question. Could you clarify? Thanks!

[@abhishekp9423]

Hi Kevin, Thanks for the awesome videos on Panda . In the second method to rename columns , we have to be cautious about the sequence in which the original name of the column has.Right??

[@dataschool]

Right!

[@abhishekp9423]

Thanks Sir

[@freeschool_]

let us suppose i have hundred columns and i have to remove all the columns from my dataset which have null values more than half of its records. How to do it? I don't want to check each column and do it drop it one by one. Please help

[@dataschool]

I think this will work: df.dropna(thresh=len(df)*0.5, axis='columns')

[@freeschool_]

@@dataschool It worked plus i found few other techniques to do that after watching other videos of you. Thanks a lot!!!

[@dataschool]

You're welcome!

[@komaljaswani7497]

awesome video as usual :D

[@dataschool]

Thanks again!

[@ChandraShekhar-ds8cp]

Hey! How can we rename column names using assign function or replace function? Is that even possible? Thanks in Adv

[@ChartExplorers]

df.columns = df.columns.str.replace('what you are replacing', 'what you want it replaced with') See 3:25 kzbin.info/www/bejne/bJatnYWMrsx4g80

[@kev5187]

Hi what if the dataframe doesn't have a name in columns how can I give names for the first time ??? Thanks

[@dataschool]

You can overwrite the columns attribute.

[@hollyzhang6491]

thanks for these wonderful videos. but here is a error I met when I run the http code:ConnectionResetError: [Errno 54] Connection reset by peer. Do you have any solutions? thanks anyway.

[@dataschool]

Sorry, I'm not sure!

[@rohiniik]

can u plz tell me how to anonymize data

[@samratchoudhury2797]

Hi, Could you tell me how can I import a binary excel file in python. excel file with extension .xlsb

[@dataschool]

I don't know if that's possible, I'm sorry!

[@alanjoseph3190]

Sir u r a very great teacher.Thanks for your class.But i have one doubt.eg: a=pd.Dataframe(['a','b',]) we get a single column.but if it is a=pd.Dataframe([['a','b']]) we get a single row.the difference only is a extra [ ].i cant understand that

[@dataschool]

Great question! The DataFrame constructor converts a Python list (your first example) to a Series. It converts a list of lists (your second example) to a DataFrame, but you only have one "inner" list so there's only one row. Try this and maybe it will make more sense: pd.DataFrame([['a','b'], ['c','d']]) Hope that helps!

[@xiao2634]

I don't get it. The type of ufo.columns is pandas.core.indexes.base.Index. I could not find this in pandas documentation. Is it a class? Where could I find the documentation of all the methods like str that I can use?

[@dataschool]

I'm actually not sure that there is documentation of everything you can do to a pandas index! I'm sorry, I just don't know.

[@xiao2634]

Thank you for your reply. I checked the source code of pandas. It is complex. pandas.core.indexes.base.Index is a class that extended several classes, one of which is StringAccessorMixin. StringAccessorMixin use another class AccessorProperty to vectorized all the methods into 'str'. All the str methods can be found at: github.com/pandas-dev/pandas/blob/master/pandas/core/strings.py

[@dataschool]

Thanks for researching this!

[@mdmantejsingh]

Hi Kevin, for me ufo.head() is not working. I am using Python 3.5.2 default editor. After saving everything when i press F5.. nothings happens. No output

[@mdmantejsingh]

I can use ipy notebook, but i want it in my default Pythons shell editor

[@dataschool]

If you're running a script, rather than running commands one by one in interactive mode, you might not see the output. I'd encourage you to run the lines of code one by one, since that tends to be most effective for data exploration.

[@mdmantejsingh]

Data School Thank you, later that day i installed ipy notebook. Your videos helped me a lot. Thank you so much.

[@dataschool]

You're very welcome!

[@swethavenkataramaniyer89]

How do I rename the data in a particular column in Python. There can be one or more records to be renamed.

[@dataschool]

You would filter and then assign... this video might help: kzbin.info/www/bejne/aHKpeIOag9NnfK8