python - Volume Overlay with Pandas -


i see in context of matplotlib , open-high-low-close, i'm wondering if can add volume overlay within pandas framework. final graph want close first 1 here: (matplotlib - finance volume overlay )

say have dataframe such:

                       num  rolling_30  rolling_10  rolling_60  volume date 2015-06-23        0.000219    0.000149    0.000168    0.000183       2 2015-06-25        0.000489    0.000162    0.000200    0.000188       3 2015-07-01        0.000164    0.000163    0.000190    0.000186       1 2015-07-02        0.000190    0.000166    0.000190    0.000187       1 2015-07-03        0.000269    0.000171    0.000198    0.000180       1 2015-07-04        0.000935    0.000196    0.000282    0.000193       2 2015-07-08        0.000154    0.000196    0.000288    0.000188       1 2015-07-11        0.000274    0.000202    0.000305    0.000190       1 2015-07-13        0.000872    0.000228    0.000380    0.000201       9

how can ['num','rolling_30','rolling_10','rolling_60'] line chart bottom of chart listing daily volume? can secondary_y volume on right, looks terrible. need traditional volume bar-graph @ bottom of chart.

the basic idea use .twinx create secondary y axis. below short sample it. graph, see left y axis price , moving averages, whereas right y axis volumn.

import pandas pd import matplotlib.pyplot plt  # data # ============================ print(df)                  num  rolling_30  rolling_10,  rolling_60  volume date                                                            2015-06-23  0.0002      0.0001       0.0002      0.0002       2 2015-06-25  0.0005      0.0002       0.0002      0.0002       3 2015-07-01  0.0002      0.0002       0.0002      0.0002       1 2015-07-02  0.0002      0.0002       0.0002      0.0002       1 2015-07-03  0.0003      0.0002       0.0002      0.0002       1 2015-07-04  0.0009      0.0002       0.0003      0.0002       2 2015-07-08  0.0002      0.0002       0.0003      0.0002       1 2015-07-11  0.0003      0.0002       0.0003      0.0002       1 2015-07-13  0.0009      0.0002       0.0004      0.0002       9  # plotting # =========================== fig, ax = plt.subplots(figsize=(10,8)) df.drop('volume', axis=1).plot(ax=ax) ax.legend(loc='best') ax2 = ax.twinx() df['volume'].plot(kind='bar', ax=ax2, color='g', alpha=0.1) ax2.set_ylim([0, ax2.get_ylim()[1] * 10]) ax2.legend(loc='best')

enter image description here


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