How to format tick labels to geo location format with python Matplotlib?












0















I am working with geo json and i have successfully drown a map according to geo json file with matplotlib and it show latitude and longitude as floating point notation such as 7.6 etc.



but my requirement is x and y axis tick labels should be format as below format.I searched in documentation but i haven't found good solution.Is there is any possible way to do that?



enter image description here










share|improve this question























  • Because the earth is not a disc, you wouldn't normally plot a map in a cartesian coordinate system. Instead a projection is usually used. We do not know about the projection you use here. But if you have a function that maps 7.6 to whatever you want to show (which isn't specified in the question either) you can use a FuncFormatter.

    – ImportanceOfBeingErnest
    Nov 14 '18 at 12:31
















0















I am working with geo json and i have successfully drown a map according to geo json file with matplotlib and it show latitude and longitude as floating point notation such as 7.6 etc.



but my requirement is x and y axis tick labels should be format as below format.I searched in documentation but i haven't found good solution.Is there is any possible way to do that?



enter image description here










share|improve this question























  • Because the earth is not a disc, you wouldn't normally plot a map in a cartesian coordinate system. Instead a projection is usually used. We do not know about the projection you use here. But if you have a function that maps 7.6 to whatever you want to show (which isn't specified in the question either) you can use a FuncFormatter.

    – ImportanceOfBeingErnest
    Nov 14 '18 at 12:31














0












0








0








I am working with geo json and i have successfully drown a map according to geo json file with matplotlib and it show latitude and longitude as floating point notation such as 7.6 etc.



but my requirement is x and y axis tick labels should be format as below format.I searched in documentation but i haven't found good solution.Is there is any possible way to do that?



enter image description here










share|improve this question














I am working with geo json and i have successfully drown a map according to geo json file with matplotlib and it show latitude and longitude as floating point notation such as 7.6 etc.



but my requirement is x and y axis tick labels should be format as below format.I searched in documentation but i haven't found good solution.Is there is any possible way to do that?



enter image description here







python python-2.7 matplotlib






share|improve this question













share|improve this question











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share|improve this question










asked Nov 14 '18 at 12:18









user3152250user3152250

156




156













  • Because the earth is not a disc, you wouldn't normally plot a map in a cartesian coordinate system. Instead a projection is usually used. We do not know about the projection you use here. But if you have a function that maps 7.6 to whatever you want to show (which isn't specified in the question either) you can use a FuncFormatter.

    – ImportanceOfBeingErnest
    Nov 14 '18 at 12:31



















  • Because the earth is not a disc, you wouldn't normally plot a map in a cartesian coordinate system. Instead a projection is usually used. We do not know about the projection you use here. But if you have a function that maps 7.6 to whatever you want to show (which isn't specified in the question either) you can use a FuncFormatter.

    – ImportanceOfBeingErnest
    Nov 14 '18 at 12:31

















Because the earth is not a disc, you wouldn't normally plot a map in a cartesian coordinate system. Instead a projection is usually used. We do not know about the projection you use here. But if you have a function that maps 7.6 to whatever you want to show (which isn't specified in the question either) you can use a FuncFormatter.

– ImportanceOfBeingErnest
Nov 14 '18 at 12:31





Because the earth is not a disc, you wouldn't normally plot a map in a cartesian coordinate system. Instead a projection is usually used. We do not know about the projection you use here. But if you have a function that maps 7.6 to whatever you want to show (which isn't specified in the question either) you can use a FuncFormatter.

– ImportanceOfBeingErnest
Nov 14 '18 at 12:31












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Actually i found an answer for this question. This kind of geo coordinates generation is not an easy task. then i substitute custom labels instead of thick values by using this.



labelsx = [item.get_text() for item in ax2.get_xticklabels()]
labelsx[1] = u'79°30'0"E'
labelsx[2] = u'80°0'0"E'
labelsx[3] = u'80°30'0"E'
labelsx[4] = u'81°0'0"E'
labelsx[5] = u'81°30'0"E'
labelsx[6] = u'82°0'0"E'
ax2.set_xticklabels(labelsx)


this not may be a good answer but , when thick labels represent same values this method is possible like this. That's why i used it here.






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    1 Answer
    1






    active

    oldest

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    1 Answer
    1






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes









    0














    Actually i found an answer for this question. This kind of geo coordinates generation is not an easy task. then i substitute custom labels instead of thick values by using this.



    labelsx = [item.get_text() for item in ax2.get_xticklabels()]
    labelsx[1] = u'79°30'0"E'
    labelsx[2] = u'80°0'0"E'
    labelsx[3] = u'80°30'0"E'
    labelsx[4] = u'81°0'0"E'
    labelsx[5] = u'81°30'0"E'
    labelsx[6] = u'82°0'0"E'
    ax2.set_xticklabels(labelsx)


    this not may be a good answer but , when thick labels represent same values this method is possible like this. That's why i used it here.






    share|improve this answer




























      0














      Actually i found an answer for this question. This kind of geo coordinates generation is not an easy task. then i substitute custom labels instead of thick values by using this.



      labelsx = [item.get_text() for item in ax2.get_xticklabels()]
      labelsx[1] = u'79°30'0"E'
      labelsx[2] = u'80°0'0"E'
      labelsx[3] = u'80°30'0"E'
      labelsx[4] = u'81°0'0"E'
      labelsx[5] = u'81°30'0"E'
      labelsx[6] = u'82°0'0"E'
      ax2.set_xticklabels(labelsx)


      this not may be a good answer but , when thick labels represent same values this method is possible like this. That's why i used it here.






      share|improve this answer


























        0












        0








        0







        Actually i found an answer for this question. This kind of geo coordinates generation is not an easy task. then i substitute custom labels instead of thick values by using this.



        labelsx = [item.get_text() for item in ax2.get_xticklabels()]
        labelsx[1] = u'79°30'0"E'
        labelsx[2] = u'80°0'0"E'
        labelsx[3] = u'80°30'0"E'
        labelsx[4] = u'81°0'0"E'
        labelsx[5] = u'81°30'0"E'
        labelsx[6] = u'82°0'0"E'
        ax2.set_xticklabels(labelsx)


        this not may be a good answer but , when thick labels represent same values this method is possible like this. That's why i used it here.






        share|improve this answer













        Actually i found an answer for this question. This kind of geo coordinates generation is not an easy task. then i substitute custom labels instead of thick values by using this.



        labelsx = [item.get_text() for item in ax2.get_xticklabels()]
        labelsx[1] = u'79°30'0"E'
        labelsx[2] = u'80°0'0"E'
        labelsx[3] = u'80°30'0"E'
        labelsx[4] = u'81°0'0"E'
        labelsx[5] = u'81°30'0"E'
        labelsx[6] = u'82°0'0"E'
        ax2.set_xticklabels(labelsx)


        this not may be a good answer but , when thick labels represent same values this method is possible like this. That's why i used it here.







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Dec 24 '18 at 16:07









        user3152250user3152250

        156




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