Manipulating multi-indices for a pandas dataframe












1












$begingroup$


I have a pandas dataframe with multi-index. I have couple of questions on this.



The indices are week numbers (38 to 42) and for each week, day of the week (DOW). So it looks like



enter image description here



The problem is the 2nd level index, that is, DofWeek, is automatically sorted in lexicographic ordering. But I want to have the usual weekdays ordering, i,e for week 39, I want it to appear as Monday, Tuesday, Wednesday, Thoursday, Friday, Saturday and Sunday and NOT in the order they appear. So when I graph it, it appears this way:
enter image description here



I want it to appear in the usual Monday, Tuesday, Wednesday etc. I have tried reindexing, but it didn't work. This is my first question.



My second question is regarding querying such dataframes. For example when I do dataframe.query('DofWeek == 'Saturday'), it is throwing an error saying Saturday is not defined. However, if I swap levels and then query, it works. For example dataframe.swaplevel().query('weekNum == 39'), it works perfectly. As far as I know, the multi-indices should be sorted in order for certain methods to work. But in my case, they are. Then why isn't it working.



Any help would be hugely appreciated.



Thanks.






python pandas







share|improve this question











$endgroup$








  • 1




    $begingroup$
    Just a heads up: you should only ask one question per question.
    $endgroup$
    – ukemi
    2 days ago
















1












$begingroup$


I have a pandas dataframe with multi-index. I have couple of questions on this.



The indices are week numbers (38 to 42) and for each week, day of the week (DOW). So it looks like



enter image description here



The problem is the 2nd level index, that is, DofWeek, is automatically sorted in lexicographic ordering. But I want to have the usual weekdays ordering, i,e for week 39, I want it to appear as Monday, Tuesday, Wednesday, Thoursday, Friday, Saturday and Sunday and NOT in the order they appear. So when I graph it, it appears this way:
enter image description here



I want it to appear in the usual Monday, Tuesday, Wednesday etc. I have tried reindexing, but it didn't work. This is my first question.



My second question is regarding querying such dataframes. For example when I do dataframe.query('DofWeek == 'Saturday'), it is throwing an error saying Saturday is not defined. However, if I swap levels and then query, it works. For example dataframe.swaplevel().query('weekNum == 39'), it works perfectly. As far as I know, the multi-indices should be sorted in order for certain methods to work. But in my case, they are. Then why isn't it working.



Any help would be hugely appreciated.



Thanks.






python pandas







share|improve this question











$endgroup$








  • 1




    $begingroup$
    Just a heads up: you should only ask one question per question.
    $endgroup$
    – ukemi
    2 days ago














1












1








1





$begingroup$


I have a pandas dataframe with multi-index. I have couple of questions on this.



The indices are week numbers (38 to 42) and for each week, day of the week (DOW). So it looks like



enter image description here



The problem is the 2nd level index, that is, DofWeek, is automatically sorted in lexicographic ordering. But I want to have the usual weekdays ordering, i,e for week 39, I want it to appear as Monday, Tuesday, Wednesday, Thoursday, Friday, Saturday and Sunday and NOT in the order they appear. So when I graph it, it appears this way:
enter image description here



I want it to appear in the usual Monday, Tuesday, Wednesday etc. I have tried reindexing, but it didn't work. This is my first question.



My second question is regarding querying such dataframes. For example when I do dataframe.query('DofWeek == 'Saturday'), it is throwing an error saying Saturday is not defined. However, if I swap levels and then query, it works. For example dataframe.swaplevel().query('weekNum == 39'), it works perfectly. As far as I know, the multi-indices should be sorted in order for certain methods to work. But in my case, they are. Then why isn't it working.



Any help would be hugely appreciated.



Thanks.






python pandas







share|improve this question











$endgroup$




I have a pandas dataframe with multi-index. I have couple of questions on this.



The indices are week numbers (38 to 42) and for each week, day of the week (DOW). So it looks like



enter image description here



The problem is the 2nd level index, that is, DofWeek, is automatically sorted in lexicographic ordering. But I want to have the usual weekdays ordering, i,e for week 39, I want it to appear as Monday, Tuesday, Wednesday, Thoursday, Friday, Saturday and Sunday and NOT in the order they appear. So when I graph it, it appears this way:
enter image description here



I want it to appear in the usual Monday, Tuesday, Wednesday etc. I have tried reindexing, but it didn't work. This is my first question.



My second question is regarding querying such dataframes. For example when I do dataframe.query('DofWeek == 'Saturday'), it is throwing an error saying Saturday is not defined. However, if I swap levels and then query, it works. For example dataframe.swaplevel().query('weekNum == 39'), it works perfectly. As far as I know, the multi-indices should be sorted in order for certain methods to work. But in my case, they are. Then why isn't it working.



Any help would be hugely appreciated.



Thanks.






python pandas




python pandas






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited 2 days ago







user62198

















asked 2 days ago









user62198user62198

4732617




4732617








  • 1




    $begingroup$
    Just a heads up: you should only ask one question per question.
    $endgroup$
    – ukemi
    2 days ago














  • 1




    $begingroup$
    Just a heads up: you should only ask one question per question.
    $endgroup$
    – ukemi
    2 days ago








1




1




$begingroup$
Just a heads up: you should only ask one question per question.
$endgroup$
– ukemi
2 days ago




$begingroup$
Just a heads up: you should only ask one question per question.
$endgroup$
– ukemi
2 days ago










1 Answer
1






active

oldest

votes


















1












$begingroup$

Ordering



You can achieve this by changing the datatype to ordered categorical:



df['DofWeek'] = pd.Categorical(

                df['DofWeek'], 

                categories=['Monday','Tuesday','Wednesday','Thursday','Friday','Saturday','Sunday'], 

                ordered=True)


And then sorting the index:



df = df.sort_index()



Error



The issue with dataframe.query('DofWeek == 'Saturday') is bad quote encapsulation. You could solve it with e.g. 'DofWeek == "Saturday"'






share|improve this answer











$endgroup$













    Your Answer





    StackExchange.ifUsing("editor", function () {
    return StackExchange.using("mathjaxEditing", function () {
    StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
    StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
    });
    });
    }, "mathjax-editing");

    StackExchange.ready(function() {
    var channelOptions = {
    tags: "".split(" "),
    id: "557"
    };
    initTagRenderer("".split(" "), "".split(" "), channelOptions);

    StackExchange.using("externalEditor", function() {
    // Have to fire editor after snippets, if snippets enabled
    if (StackExchange.settings.snippets.snippetsEnabled) {
    StackExchange.using("snippets", function() {
    createEditor();
    });
    }
    else {
    createEditor();
    }
    });

    function createEditor() {
    StackExchange.prepareEditor({
    heartbeatType: 'answer',
    autoActivateHeartbeat: false,
    convertImagesToLinks: false,
    noModals: true,
    showLowRepImageUploadWarning: true,
    reputationToPostImages: null,
    bindNavPrevention: true,
    postfix: "",
    imageUploader: {
    brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
    contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
    allowUrls: true
    },
    onDemand: true,
    discardSelector: ".discard-answer"
    ,immediatelyShowMarkdownHelp:true
    });


    }
    });














    draft saved

    draft discarded


















    StackExchange.ready(
    function () {
    StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f47363%2fmanipulating-multi-indices-for-a-pandas-dataframe%23new-answer', 'question_page');
    }
    );

    Post as a guest















    Required, but never shown

























    1 Answer
    1






    active

    oldest

    votes








    1 Answer
    1






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes









    1












    $begingroup$

    Ordering



    You can achieve this by changing the datatype to ordered categorical:



    df['DofWeek'] = pd.Categorical(
    
                df['DofWeek'], 
    
                categories=['Monday','Tuesday','Wednesday','Thursday','Friday','Saturday','Sunday'], 
    
                ordered=True)


    And then sorting the index:



    df = df.sort_index()



    Error



    The issue with dataframe.query('DofWeek == 'Saturday') is bad quote encapsulation. You could solve it with e.g. 'DofWeek == "Saturday"'






    share|improve this answer











    $endgroup$


















      1












      $begingroup$

      Ordering



      You can achieve this by changing the datatype to ordered categorical:



      df['DofWeek'] = pd.Categorical(
      
                df['DofWeek'], 
      
                categories=['Monday','Tuesday','Wednesday','Thursday','Friday','Saturday','Sunday'], 
      
                ordered=True)


      And then sorting the index:



      df = df.sort_index()



      Error



      The issue with dataframe.query('DofWeek == 'Saturday') is bad quote encapsulation. You could solve it with e.g. 'DofWeek == "Saturday"'






      share|improve this answer











      $endgroup$
















        1












        1








        1





        $begingroup$

        Ordering



        You can achieve this by changing the datatype to ordered categorical:



        df['DofWeek'] = pd.Categorical(
        
                df['DofWeek'], 
        
                categories=['Monday','Tuesday','Wednesday','Thursday','Friday','Saturday','Sunday'], 
        
                ordered=True)


        And then sorting the index:



        df = df.sort_index()



        Error



        The issue with dataframe.query('DofWeek == 'Saturday') is bad quote encapsulation. You could solve it with e.g. 'DofWeek == "Saturday"'






        share|improve this answer











        $endgroup$



        Ordering



        You can achieve this by changing the datatype to ordered categorical:



        df['DofWeek'] = pd.Categorical(
        
                df['DofWeek'], 
        
                categories=['Monday','Tuesday','Wednesday','Thursday','Friday','Saturday','Sunday'], 
        
                ordered=True)


        And then sorting the index:



        df = df.sort_index()



        Error



        The issue with dataframe.query('DofWeek == 'Saturday') is bad quote encapsulation. You could solve it with e.g. 'DofWeek == "Saturday"'







        share|improve this answer














        share|improve this answer



        share|improve this answer








        edited 2 days ago

























        answered 2 days ago









        ukemiukemi

        1488




        1488






























            draft saved

            draft discarded




















































            Thanks for contributing an answer to Data Science Stack Exchange!


            • Please be sure to answer the question. Provide details and share your research!

            But avoid …



            • Asking for help, clarification, or responding to other answers.

            • Making statements based on opinion; back them up with references or personal experience.


            Use MathJax to format equations. MathJax reference.


            To learn more, see our tips on writing great answers.




            draft saved


            draft discarded














            StackExchange.ready(
            function () {
            StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f47363%2fmanipulating-multi-indices-for-a-pandas-dataframe%23new-answer', 'question_page');
            }
            );

            Post as a guest















            Required, but never shown





















































            Required, but never shown














            Required, but never shown












            Required, but never shown







            Required, but never shown

































            Required, but never shown














            Required, but never shown












            Required, but never shown







            Required, but never shown







            -

            Popular posts from this blog

            How to label and detect the document text images

            Image
            1 $begingroup$ This is what I mean as document text image: I want to label the texts in image as separate blocks and my model should detect these labels as classes. NOTE: This is how the end result should be like: The labels like Block 1, Block 2, Block 3,.. should be Logo, Title, Date,.. Others, etc. Work done: First approach : I tried to implement this method via Object Detection, it didn't work. It didn't even detect any text. Second approach : Then I tried it using PixelLink. As this model is build for scene text detection, it detected each and every text in the image. But this method can detect multiple lines of text if the threshold values are increased. But I have no idea how do I add labels to the text blocks. PIXEL_CLS_WEIGHT_all_ones = 'PIXEL_CLS_WEIGHT_all_ones' PIXEL_C...
            Read more

            Vallis Paradisi

            Image
            Coordinata: .mw-parser-output .geo-default,.mw-parser-output .geo-dms,.mw-parser-output .geo-dec{display:inline}.mw-parser-output .geo-nondefault,.mw-parser-output .geo-multi-punct{display:none}.mw-parser-output .longitude,.mw-parser-output .latitude{white-space:nowrap} 33°03′S 71°37′W  /  33.05°S 71.617°W  / -33.05; -71.617 Vallis Paradisi Res apud Vicidata repertae: Civitas : Chilia Numerus incolarum : 296 655 Zona horaria : UTC-4 Situs interretialis Nomen officiale : Valparaíso Gubernium Consilium : municipal council of Valparaíso Geographia Superficies : 401 600 000 Metrum quadratum Coniunctiones urbium Urbes gemellae : Ovetum , Badalona , Santa Fe , Ora longa , Sciamhaevum , Quantunia , Callao , Bat Yam , Melaka , Novorossiysk , Busan , Corduba , Odessa , Rosario , Malacca , Barcino , Soteropolis , Franciscopolis (California) , Guanajuato, Silao Tabula aut despectus Despectus in portum sinumque et urbem Vallis Paradisi Vallis Para...
            Read more

            Tabula Rosettana

            Image
            Tabula multilinguis Rosettana in Museo Britannico ostenditur. Tabula Rosettana, [1] etiam titulo OGIS 90 agnita, est stela decreto de rebus sacris in Aegypto anno 196 a.C.n. lato inscripta. Tabula iuxta Rosettam Aegypti, urbem in delta Nili et ad oram maris Mediterranei iacentem, anno 1799 a milite Francico reperta est. Inventio stelae, linguis duabus scripturisque tribus inscriptae, eruditis Instituti Aegypti statim nuntiata est; ibi enim iussu imperatoris Napoleonis eruditi omnium scientiarum (sub aegide Commissionis Scientiarum et Artium) properaverant cum expeditione Francica. Qua a Britannis mox debellata, tabula Rosettana Londinium missa hodie apud Museum Britannicum iacet. Textus Graecus cito lectus interpretationi textuum Aegyptiorum (in formis hieroglyphica et demotica expressorum) gradatim adiuvit. Denique textum plene interpretatus est Ioannes Franciscus Champollion. Ab opere eruditorum cumulativo coepit hodiernus scripturae hieroglyphicae linguaeque Aegyptiae a...
            Read more