multiple matplotlib subplots: interleave pandas dataframe HTML with each subplot












0















I have a pandas.DataFrame with multiple rows (1 per trade I want to inspect)



trades = pandas.read_csv(...)


I want to plot each trade on a matplotlib subplot. I create a pyplot.figure using len(trades) to create sufficient height



fig = pyplot.figure(figsize=(40,15 * len(trades)))


I then iterate over each trade and generate a plot



for i,r in enumerate(trades.iterrows()):
_, trade = r

start = trade.open_time - datetime.timedelta(seconds=30)
end = trade.close_time + datetime.timedelta(seconds=30)

b = bids[start:end]
a = asks[start:end]

ax = fig.add_subplot(len(trades),1,i+1)

# plot bid/ask
ax.plot_date(b.index, b, fmt='-', label='bid')
ax.plot_date(a.index, a, fmt='-', label='ask')

# plot entry/exit markers
ax.plot(trade.open_time, trade.open_price, marker='o', color='b')
ax.plot(trade.close_time, trade.close_price, marker='o', color='r')

ax.set_title("Trade {}".format(i+1, fontsize=10)
ax.set_xlabel("Date")
ax.set_ylabel("Price")

ax.legend(loc='best', fontsize='large')

pyplot.show()

# free resources
pyplot.close(fig.number)


This works great.



Now, however, I want to display the rendered HTML of the dataframe for the trade in question.



Since I am doing this in a jupyter notebook, from this SO answer I was able to find the following snippet which will display my dataframe in html:



t = pandas.DataFrame(trades.iloc[i]).T
IPython.display.display(IPython.display.HTML(t.to_html())


I insert this snippet into my loop.



The problem is that each trade's rendered HTML dataframe is printed one-after-the-other, and then after all of the dataframes have been printed, the plots are printed.



+-----------+
| dataframe |
+-----------+
+-----------+
| dataframe |
+-----------+
+-----------+
| dataframe |
+-----------+
+------+
| |
| plot |
| |
+------+
+------+
| |
| plot |
| |
+------+
+------+
| |
| plot |
| |
+------+


Given I have created a single large pyplot.figure, and I call pyplot.show() after the loop, this makes sense - inside the loop I output the dataframe HTML, and after the loop I display the plot.



Question:



How can I interleave the notebook HTML and each subplot?



+-----------+
| dataframe |
+-----------+
+------+
| |
| plot |
| |
+------+
+-----------+
| dataframe |
+-----------+
+------+
| |
| plot |
| |
+------+
+-----------+
| dataframe |
+-----------+
+------+
| |
| plot |
| |
+------+









share|improve this question



























    0















    I have a pandas.DataFrame with multiple rows (1 per trade I want to inspect)



    trades = pandas.read_csv(...)


    I want to plot each trade on a matplotlib subplot. I create a pyplot.figure using len(trades) to create sufficient height



    fig = pyplot.figure(figsize=(40,15 * len(trades)))


    I then iterate over each trade and generate a plot



    for i,r in enumerate(trades.iterrows()):
    _, trade = r

    start = trade.open_time - datetime.timedelta(seconds=30)
    end = trade.close_time + datetime.timedelta(seconds=30)

    b = bids[start:end]
    a = asks[start:end]

    ax = fig.add_subplot(len(trades),1,i+1)

    # plot bid/ask
    ax.plot_date(b.index, b, fmt='-', label='bid')
    ax.plot_date(a.index, a, fmt='-', label='ask')

    # plot entry/exit markers
    ax.plot(trade.open_time, trade.open_price, marker='o', color='b')
    ax.plot(trade.close_time, trade.close_price, marker='o', color='r')

    ax.set_title("Trade {}".format(i+1, fontsize=10)
    ax.set_xlabel("Date")
    ax.set_ylabel("Price")

    ax.legend(loc='best', fontsize='large')

    pyplot.show()

    # free resources
    pyplot.close(fig.number)


    This works great.



    Now, however, I want to display the rendered HTML of the dataframe for the trade in question.



    Since I am doing this in a jupyter notebook, from this SO answer I was able to find the following snippet which will display my dataframe in html:



    t = pandas.DataFrame(trades.iloc[i]).T
    IPython.display.display(IPython.display.HTML(t.to_html())


    I insert this snippet into my loop.



    The problem is that each trade's rendered HTML dataframe is printed one-after-the-other, and then after all of the dataframes have been printed, the plots are printed.



    +-----------+
    | dataframe |
    +-----------+
    +-----------+
    | dataframe |
    +-----------+
    +-----------+
    | dataframe |
    +-----------+
    +------+
    | |
    | plot |
    | |
    +------+
    +------+
    | |
    | plot |
    | |
    +------+
    +------+
    | |
    | plot |
    | |
    +------+


    Given I have created a single large pyplot.figure, and I call pyplot.show() after the loop, this makes sense - inside the loop I output the dataframe HTML, and after the loop I display the plot.



    Question:



    How can I interleave the notebook HTML and each subplot?



    +-----------+
    | dataframe |
    +-----------+
    +------+
    | |
    | plot |
    | |
    +------+
    +-----------+
    | dataframe |
    +-----------+
    +------+
    | |
    | plot |
    | |
    +------+
    +-----------+
    | dataframe |
    +-----------+
    +------+
    | |
    | plot |
    | |
    +------+









    share|improve this question

























      0












      0








      0








      I have a pandas.DataFrame with multiple rows (1 per trade I want to inspect)



      trades = pandas.read_csv(...)


      I want to plot each trade on a matplotlib subplot. I create a pyplot.figure using len(trades) to create sufficient height



      fig = pyplot.figure(figsize=(40,15 * len(trades)))


      I then iterate over each trade and generate a plot



      for i,r in enumerate(trades.iterrows()):
      _, trade = r

      start = trade.open_time - datetime.timedelta(seconds=30)
      end = trade.close_time + datetime.timedelta(seconds=30)

      b = bids[start:end]
      a = asks[start:end]

      ax = fig.add_subplot(len(trades),1,i+1)

      # plot bid/ask
      ax.plot_date(b.index, b, fmt='-', label='bid')
      ax.plot_date(a.index, a, fmt='-', label='ask')

      # plot entry/exit markers
      ax.plot(trade.open_time, trade.open_price, marker='o', color='b')
      ax.plot(trade.close_time, trade.close_price, marker='o', color='r')

      ax.set_title("Trade {}".format(i+1, fontsize=10)
      ax.set_xlabel("Date")
      ax.set_ylabel("Price")

      ax.legend(loc='best', fontsize='large')

      pyplot.show()

      # free resources
      pyplot.close(fig.number)


      This works great.



      Now, however, I want to display the rendered HTML of the dataframe for the trade in question.



      Since I am doing this in a jupyter notebook, from this SO answer I was able to find the following snippet which will display my dataframe in html:



      t = pandas.DataFrame(trades.iloc[i]).T
      IPython.display.display(IPython.display.HTML(t.to_html())


      I insert this snippet into my loop.



      The problem is that each trade's rendered HTML dataframe is printed one-after-the-other, and then after all of the dataframes have been printed, the plots are printed.



      +-----------+
      | dataframe |
      +-----------+
      +-----------+
      | dataframe |
      +-----------+
      +-----------+
      | dataframe |
      +-----------+
      +------+
      | |
      | plot |
      | |
      +------+
      +------+
      | |
      | plot |
      | |
      +------+
      +------+
      | |
      | plot |
      | |
      +------+


      Given I have created a single large pyplot.figure, and I call pyplot.show() after the loop, this makes sense - inside the loop I output the dataframe HTML, and after the loop I display the plot.



      Question:



      How can I interleave the notebook HTML and each subplot?



      +-----------+
      | dataframe |
      +-----------+
      +------+
      | |
      | plot |
      | |
      +------+
      +-----------+
      | dataframe |
      +-----------+
      +------+
      | |
      | plot |
      | |
      +------+
      +-----------+
      | dataframe |
      +-----------+
      +------+
      | |
      | plot |
      | |
      +------+









      share|improve this question














      I have a pandas.DataFrame with multiple rows (1 per trade I want to inspect)



      trades = pandas.read_csv(...)


      I want to plot each trade on a matplotlib subplot. I create a pyplot.figure using len(trades) to create sufficient height



      fig = pyplot.figure(figsize=(40,15 * len(trades)))


      I then iterate over each trade and generate a plot



      for i,r in enumerate(trades.iterrows()):
      _, trade = r

      start = trade.open_time - datetime.timedelta(seconds=30)
      end = trade.close_time + datetime.timedelta(seconds=30)

      b = bids[start:end]
      a = asks[start:end]

      ax = fig.add_subplot(len(trades),1,i+1)

      # plot bid/ask
      ax.plot_date(b.index, b, fmt='-', label='bid')
      ax.plot_date(a.index, a, fmt='-', label='ask')

      # plot entry/exit markers
      ax.plot(trade.open_time, trade.open_price, marker='o', color='b')
      ax.plot(trade.close_time, trade.close_price, marker='o', color='r')

      ax.set_title("Trade {}".format(i+1, fontsize=10)
      ax.set_xlabel("Date")
      ax.set_ylabel("Price")

      ax.legend(loc='best', fontsize='large')

      pyplot.show()

      # free resources
      pyplot.close(fig.number)


      This works great.



      Now, however, I want to display the rendered HTML of the dataframe for the trade in question.



      Since I am doing this in a jupyter notebook, from this SO answer I was able to find the following snippet which will display my dataframe in html:



      t = pandas.DataFrame(trades.iloc[i]).T
      IPython.display.display(IPython.display.HTML(t.to_html())


      I insert this snippet into my loop.



      The problem is that each trade's rendered HTML dataframe is printed one-after-the-other, and then after all of the dataframes have been printed, the plots are printed.



      +-----------+
      | dataframe |
      +-----------+
      +-----------+
      | dataframe |
      +-----------+
      +-----------+
      | dataframe |
      +-----------+
      +------+
      | |
      | plot |
      | |
      +------+
      +------+
      | |
      | plot |
      | |
      +------+
      +------+
      | |
      | plot |
      | |
      +------+


      Given I have created a single large pyplot.figure, and I call pyplot.show() after the loop, this makes sense - inside the loop I output the dataframe HTML, and after the loop I display the plot.



      Question:



      How can I interleave the notebook HTML and each subplot?



      +-----------+
      | dataframe |
      +-----------+
      +------+
      | |
      | plot |
      | |
      +------+
      +-----------+
      | dataframe |
      +-----------+
      +------+
      | |
      | plot |
      | |
      +------+
      +-----------+
      | dataframe |
      +-----------+
      +------+
      | |
      | plot |
      | |
      +------+






      python pandas matplotlib jupyter-notebook






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 21 '18 at 22:51









      Steve LorimerSteve Lorimer

      12.7k1267142




      12.7k1267142
























          1 Answer
          1






          active

          oldest

          votes


















          1














          I believe you need to create three separate figures and call plt.show() within the loop. Something like this (side note, I don't think one needs pyplot.close using the Jupyter notebook frontend):



          trades = pandas.read_csv(...)

          for i, r in enumerate(trades.iterrows()):
          _, trade = r

          start = trade.open_time - datetime.timedelta(seconds=30)
          end = trade.close_time + datetime.timedelta(seconds=30)

          b = bids[start:end]
          a = asks[start:end]

          fig, ax = plt.subplots(figsize=(40, 15))

          # plot bid/ask
          ax.plot_date(b.index, b, fmt='-', label='bid')
          ax.plot_date(a.index, a, fmt='-', label='ask')

          # plot entry/exit markers
          ax.plot(trade.open_time, trade.open_price, marker='o', color='b')
          ax.plot(trade.close_time, trade.close_price, marker='o', color='r')

          ax.set_title("Trade {}".format(i+1, fontsize=10))
          ax.set_xlabel("Date")
          ax.set_ylabel("Price")

          ax.legend(loc='best', fontsize='large')

          t = pandas.DataFrame(trades.iloc[i]).T
          IPython.display.display(IPython.display.HTML(t.to_html())

          pyplot.show()





          share|improve this answer



















          • 1





            damn, it's so obvious! Thank you!

            – Steve Lorimer
            Nov 21 '18 at 22:59






          • 1





            @SteveLorimer, you're welcome, and happy coding!

            – Peter Leimbigler
            Nov 21 '18 at 23:00











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          1 Answer
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          active

          oldest

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          1 Answer
          1






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          1














          I believe you need to create three separate figures and call plt.show() within the loop. Something like this (side note, I don't think one needs pyplot.close using the Jupyter notebook frontend):



          trades = pandas.read_csv(...)

          for i, r in enumerate(trades.iterrows()):
          _, trade = r

          start = trade.open_time - datetime.timedelta(seconds=30)
          end = trade.close_time + datetime.timedelta(seconds=30)

          b = bids[start:end]
          a = asks[start:end]

          fig, ax = plt.subplots(figsize=(40, 15))

          # plot bid/ask
          ax.plot_date(b.index, b, fmt='-', label='bid')
          ax.plot_date(a.index, a, fmt='-', label='ask')

          # plot entry/exit markers
          ax.plot(trade.open_time, trade.open_price, marker='o', color='b')
          ax.plot(trade.close_time, trade.close_price, marker='o', color='r')

          ax.set_title("Trade {}".format(i+1, fontsize=10))
          ax.set_xlabel("Date")
          ax.set_ylabel("Price")

          ax.legend(loc='best', fontsize='large')

          t = pandas.DataFrame(trades.iloc[i]).T
          IPython.display.display(IPython.display.HTML(t.to_html())

          pyplot.show()





          share|improve this answer



















          • 1





            damn, it's so obvious! Thank you!

            – Steve Lorimer
            Nov 21 '18 at 22:59






          • 1





            @SteveLorimer, you're welcome, and happy coding!

            – Peter Leimbigler
            Nov 21 '18 at 23:00
















          1














          I believe you need to create three separate figures and call plt.show() within the loop. Something like this (side note, I don't think one needs pyplot.close using the Jupyter notebook frontend):



          trades = pandas.read_csv(...)

          for i, r in enumerate(trades.iterrows()):
          _, trade = r

          start = trade.open_time - datetime.timedelta(seconds=30)
          end = trade.close_time + datetime.timedelta(seconds=30)

          b = bids[start:end]
          a = asks[start:end]

          fig, ax = plt.subplots(figsize=(40, 15))

          # plot bid/ask
          ax.plot_date(b.index, b, fmt='-', label='bid')
          ax.plot_date(a.index, a, fmt='-', label='ask')

          # plot entry/exit markers
          ax.plot(trade.open_time, trade.open_price, marker='o', color='b')
          ax.plot(trade.close_time, trade.close_price, marker='o', color='r')

          ax.set_title("Trade {}".format(i+1, fontsize=10))
          ax.set_xlabel("Date")
          ax.set_ylabel("Price")

          ax.legend(loc='best', fontsize='large')

          t = pandas.DataFrame(trades.iloc[i]).T
          IPython.display.display(IPython.display.HTML(t.to_html())

          pyplot.show()





          share|improve this answer



















          • 1





            damn, it's so obvious! Thank you!

            – Steve Lorimer
            Nov 21 '18 at 22:59






          • 1





            @SteveLorimer, you're welcome, and happy coding!

            – Peter Leimbigler
            Nov 21 '18 at 23:00














          1












          1








          1







          I believe you need to create three separate figures and call plt.show() within the loop. Something like this (side note, I don't think one needs pyplot.close using the Jupyter notebook frontend):



          trades = pandas.read_csv(...)

          for i, r in enumerate(trades.iterrows()):
          _, trade = r

          start = trade.open_time - datetime.timedelta(seconds=30)
          end = trade.close_time + datetime.timedelta(seconds=30)

          b = bids[start:end]
          a = asks[start:end]

          fig, ax = plt.subplots(figsize=(40, 15))

          # plot bid/ask
          ax.plot_date(b.index, b, fmt='-', label='bid')
          ax.plot_date(a.index, a, fmt='-', label='ask')

          # plot entry/exit markers
          ax.plot(trade.open_time, trade.open_price, marker='o', color='b')
          ax.plot(trade.close_time, trade.close_price, marker='o', color='r')

          ax.set_title("Trade {}".format(i+1, fontsize=10))
          ax.set_xlabel("Date")
          ax.set_ylabel("Price")

          ax.legend(loc='best', fontsize='large')

          t = pandas.DataFrame(trades.iloc[i]).T
          IPython.display.display(IPython.display.HTML(t.to_html())

          pyplot.show()





          share|improve this answer













          I believe you need to create three separate figures and call plt.show() within the loop. Something like this (side note, I don't think one needs pyplot.close using the Jupyter notebook frontend):



          trades = pandas.read_csv(...)

          for i, r in enumerate(trades.iterrows()):
          _, trade = r

          start = trade.open_time - datetime.timedelta(seconds=30)
          end = trade.close_time + datetime.timedelta(seconds=30)

          b = bids[start:end]
          a = asks[start:end]

          fig, ax = plt.subplots(figsize=(40, 15))

          # plot bid/ask
          ax.plot_date(b.index, b, fmt='-', label='bid')
          ax.plot_date(a.index, a, fmt='-', label='ask')

          # plot entry/exit markers
          ax.plot(trade.open_time, trade.open_price, marker='o', color='b')
          ax.plot(trade.close_time, trade.close_price, marker='o', color='r')

          ax.set_title("Trade {}".format(i+1, fontsize=10))
          ax.set_xlabel("Date")
          ax.set_ylabel("Price")

          ax.legend(loc='best', fontsize='large')

          t = pandas.DataFrame(trades.iloc[i]).T
          IPython.display.display(IPython.display.HTML(t.to_html())

          pyplot.show()






          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Nov 21 '18 at 22:57









          Peter LeimbiglerPeter Leimbigler

          4,5331416




          4,5331416








          • 1





            damn, it's so obvious! Thank you!

            – Steve Lorimer
            Nov 21 '18 at 22:59






          • 1





            @SteveLorimer, you're welcome, and happy coding!

            – Peter Leimbigler
            Nov 21 '18 at 23:00














          • 1





            damn, it's so obvious! Thank you!

            – Steve Lorimer
            Nov 21 '18 at 22:59






          • 1





            @SteveLorimer, you're welcome, and happy coding!

            – Peter Leimbigler
            Nov 21 '18 at 23:00








          1




          1





          damn, it's so obvious! Thank you!

          – Steve Lorimer
          Nov 21 '18 at 22:59





          damn, it's so obvious! Thank you!

          – Steve Lorimer
          Nov 21 '18 at 22:59




          1




          1





          @SteveLorimer, you're welcome, and happy coding!

          – Peter Leimbigler
          Nov 21 '18 at 23:00





          @SteveLorimer, you're welcome, and happy coding!

          – Peter Leimbigler
          Nov 21 '18 at 23:00




















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