Plotting time in x axis using matplotlib












2















I have the following dataset:



pressuredfjan1[['Unit','Time1']].head()
Out[53]:
Unit Time1
0 321.3599 1970-01-01 00:00:40
1 321.3599 1970-01-01 00:04:40
2 321.6651 1970-01-01 00:06:40
3 320.7496 1970-01-01 00:10:40
4 322.2755 1970-01-01 00:14:40


I am trying to plot Unit against Time1 in an HH:MM:SS format.
I've tried the following code:



dates = dates.date2num(list(pressuredfjan1['Time1']))
fig = plt.figure(figsize=(20,10))
ax1 = fig.add_subplot(111)
ax1.plot(dates,pressuredfjan1['Unit'])
plt.show()


This gives me the plot, but I am not getting HH:MM:SS format in the x-axis. Instead, I'm getting 3.1, 3.2, 3.4...Le14 etc. Can somebody help me out here please? Thanks.










share|improve this question





























    2















    I have the following dataset:



    pressuredfjan1[['Unit','Time1']].head()
    Out[53]:
    Unit Time1
    0 321.3599 1970-01-01 00:00:40
    1 321.3599 1970-01-01 00:04:40
    2 321.6651 1970-01-01 00:06:40
    3 320.7496 1970-01-01 00:10:40
    4 322.2755 1970-01-01 00:14:40


    I am trying to plot Unit against Time1 in an HH:MM:SS format.
    I've tried the following code:



    dates = dates.date2num(list(pressuredfjan1['Time1']))
    fig = plt.figure(figsize=(20,10))
    ax1 = fig.add_subplot(111)
    ax1.plot(dates,pressuredfjan1['Unit'])
    plt.show()


    This gives me the plot, but I am not getting HH:MM:SS format in the x-axis. Instead, I'm getting 3.1, 3.2, 3.4...Le14 etc. Can somebody help me out here please? Thanks.










    share|improve this question



























      2












      2








      2


      1






      I have the following dataset:



      pressuredfjan1[['Unit','Time1']].head()
      Out[53]:
      Unit Time1
      0 321.3599 1970-01-01 00:00:40
      1 321.3599 1970-01-01 00:04:40
      2 321.6651 1970-01-01 00:06:40
      3 320.7496 1970-01-01 00:10:40
      4 322.2755 1970-01-01 00:14:40


      I am trying to plot Unit against Time1 in an HH:MM:SS format.
      I've tried the following code:



      dates = dates.date2num(list(pressuredfjan1['Time1']))
      fig = plt.figure(figsize=(20,10))
      ax1 = fig.add_subplot(111)
      ax1.plot(dates,pressuredfjan1['Unit'])
      plt.show()


      This gives me the plot, but I am not getting HH:MM:SS format in the x-axis. Instead, I'm getting 3.1, 3.2, 3.4...Le14 etc. Can somebody help me out here please? Thanks.










      share|improve this question
















      I have the following dataset:



      pressuredfjan1[['Unit','Time1']].head()
      Out[53]:
      Unit Time1
      0 321.3599 1970-01-01 00:00:40
      1 321.3599 1970-01-01 00:04:40
      2 321.6651 1970-01-01 00:06:40
      3 320.7496 1970-01-01 00:10:40
      4 322.2755 1970-01-01 00:14:40


      I am trying to plot Unit against Time1 in an HH:MM:SS format.
      I've tried the following code:



      dates = dates.date2num(list(pressuredfjan1['Time1']))
      fig = plt.figure(figsize=(20,10))
      ax1 = fig.add_subplot(111)
      ax1.plot(dates,pressuredfjan1['Unit'])
      plt.show()


      This gives me the plot, but I am not getting HH:MM:SS format in the x-axis. Instead, I'm getting 3.1, 3.2, 3.4...Le14 etc. Can somebody help me out here please? Thanks.







      python datetime matplotlib timedelta






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      edited Nov 14 '18 at 10:00









      Joe

      5,96421329




      5,96421329










      asked Nov 14 '18 at 7:23









      IndigoChildIndigoChild

      340212




      340212
























          1 Answer
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          1














          You can use:



          import matplotlib as mpl

          pressuredfjan1['dates'] = pd.to_datetime(pressuredfjan1['Time1']).dt.strftime('%H:%M:%S')
          fig = plt.figure(figsize=(20,10))
          ax1 = fig.add_subplot(111)
          majorFormatter = mpl.dates.DateFormatter('%H:%M:%S')
          ax1.xaxis.set_major_formatter(majorFormatter)
          plt.plot_date(pressuredfjan1['dates'], pressuredfjan1['Unit'])
          plt.show()


          enter image description here






          share|improve this answer
























          • Thanks a lot ! :)

            – IndigoChild
            Nov 14 '18 at 9:30











          • You aer welcome! :)

            – Joe
            Nov 14 '18 at 9:30











          Your Answer






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          1 Answer
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          1 Answer
          1






          active

          oldest

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          active

          oldest

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          active

          oldest

          votes









          1














          You can use:



          import matplotlib as mpl

          pressuredfjan1['dates'] = pd.to_datetime(pressuredfjan1['Time1']).dt.strftime('%H:%M:%S')
          fig = plt.figure(figsize=(20,10))
          ax1 = fig.add_subplot(111)
          majorFormatter = mpl.dates.DateFormatter('%H:%M:%S')
          ax1.xaxis.set_major_formatter(majorFormatter)
          plt.plot_date(pressuredfjan1['dates'], pressuredfjan1['Unit'])
          plt.show()


          enter image description here






          share|improve this answer
























          • Thanks a lot ! :)

            – IndigoChild
            Nov 14 '18 at 9:30











          • You aer welcome! :)

            – Joe
            Nov 14 '18 at 9:30
















          1














          You can use:



          import matplotlib as mpl

          pressuredfjan1['dates'] = pd.to_datetime(pressuredfjan1['Time1']).dt.strftime('%H:%M:%S')
          fig = plt.figure(figsize=(20,10))
          ax1 = fig.add_subplot(111)
          majorFormatter = mpl.dates.DateFormatter('%H:%M:%S')
          ax1.xaxis.set_major_formatter(majorFormatter)
          plt.plot_date(pressuredfjan1['dates'], pressuredfjan1['Unit'])
          plt.show()


          enter image description here






          share|improve this answer
























          • Thanks a lot ! :)

            – IndigoChild
            Nov 14 '18 at 9:30











          • You aer welcome! :)

            – Joe
            Nov 14 '18 at 9:30














          1












          1








          1







          You can use:



          import matplotlib as mpl

          pressuredfjan1['dates'] = pd.to_datetime(pressuredfjan1['Time1']).dt.strftime('%H:%M:%S')
          fig = plt.figure(figsize=(20,10))
          ax1 = fig.add_subplot(111)
          majorFormatter = mpl.dates.DateFormatter('%H:%M:%S')
          ax1.xaxis.set_major_formatter(majorFormatter)
          plt.plot_date(pressuredfjan1['dates'], pressuredfjan1['Unit'])
          plt.show()


          enter image description here






          share|improve this answer













          You can use:



          import matplotlib as mpl

          pressuredfjan1['dates'] = pd.to_datetime(pressuredfjan1['Time1']).dt.strftime('%H:%M:%S')
          fig = plt.figure(figsize=(20,10))
          ax1 = fig.add_subplot(111)
          majorFormatter = mpl.dates.DateFormatter('%H:%M:%S')
          ax1.xaxis.set_major_formatter(majorFormatter)
          plt.plot_date(pressuredfjan1['dates'], pressuredfjan1['Unit'])
          plt.show()


          enter image description here







          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Nov 14 '18 at 7:55









          JoeJoe

          5,96421329




          5,96421329













          • Thanks a lot ! :)

            – IndigoChild
            Nov 14 '18 at 9:30











          • You aer welcome! :)

            – Joe
            Nov 14 '18 at 9:30



















          • Thanks a lot ! :)

            – IndigoChild
            Nov 14 '18 at 9:30











          • You aer welcome! :)

            – Joe
            Nov 14 '18 at 9:30

















          Thanks a lot ! :)

          – IndigoChild
          Nov 14 '18 at 9:30





          Thanks a lot ! :)

          – IndigoChild
          Nov 14 '18 at 9:30













          You aer welcome! :)

          – Joe
          Nov 14 '18 at 9:30





          You aer welcome! :)

          – Joe
          Nov 14 '18 at 9:30


















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