具有不同 y 轴的同一可视化中的 2 个线图

Question

I am quite stuck with this one. I am trying to create a line diagram with the same x-axis scale (years) but a different y-axis scale How can I do that?

I have two datasets with this info:

test_data1.head()
   latitude longitude   place       year
0   36.087  -106.168    New Mexico  1973
1   33.917  -90.775     Mississippi 1973
2   37.160  -104.594    Colorado    1973
3   37.148  -104.571    Colorado    1973
4   36.500  -100.693    Oklahoma    1974

test_data2.head()
    LAT          LONG       BBLS    Year
0   36.900324   -98.21826   300     1977.0
1   36.896636   -98.17772   1,000   2002.0
2   36.806113   -98.32584   1,000   1988.0
3   36.888589   -98.31853   1,000   1985.0
4   36.892128   -98.19462   2,400   2002.0

for context, test_data1 refers to earthquakes and test_data2 refers to injection wells and BBLS is the number of barrels produced.

What I want to do is create a line diagram showing the number of earthquakes per year, and the number of barrels produced per year from 1980. I want to display the number of earthquakes per year on the left (y1) and the number of barrels produced per year on the right (y2).

Here's what I've done but it didn't work, anyone knows why or show me a way to do it?

import matplotlib.pyplot as plt
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()
%matplotlib  inline 

x=test_data1['year']
y1 = test_data1['place']
y2 = test_data2['BBLS']

fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
curve1 = ax1.plot (x, y1, label='Number of Earthquakes', color='r')
curve2= ax2.plot (x, y2, label='Number of Barrels Produced', color='b')
plt.plot()
plt.show()

I'm getting this huge error but I can't understand it since I am new to Python:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-109-9e26d5f7e5e2> in <module>
     11 ax2 = ax1.twinx()
     12 curve1 = ax1.plot (x, y1, label='Number of Earthquakes', color='r')
---> 13 curve2= ax2.plot (x, y2, label='Number of Barrels Produced', color='b')
     14 plt.plot()
     15 plt.show()

~\anaconda3\lib\site-packages\matplotlib\axes\_axes.py in plot(self, scalex, scaley, data, *args, **kwargs)
   1741         """
   1742         kwargs = cbook.normalize_kwargs(kwargs, mlines.Line2D)
-> 1743         lines = [*self._get_lines(*args, data=data, **kwargs)]
   1744         for line in lines:
   1745             self.add_line(line)

~\anaconda3\lib\site-packages\matplotlib\axes\_base.py in __call__(self, data, *args, **kwargs)
    271                 this += args[0],
    272                 args = args[1:]
--> 273             yield from self._plot_args(this, kwargs)
    274 
    275     def get_next_color(self):

~\anaconda3\lib\site-packages\matplotlib\axes\_base.py in _plot_args(self, tup, kwargs)
    394             self.axes.xaxis.update_units(x)
    395         if self.axes.yaxis is not None:
--> 396             self.axes.yaxis.update_units(y)
    397 
    398         if x.shape[0] != y.shape[0]:

~\anaconda3\lib\site-packages\matplotlib\axis.py in update_units(self, data)
   1461         neednew = self.converter != converter
   1462         self.converter = converter
-> 1463         default = self.converter.default_units(data, self)
   1464         if default is not None and self.units is None:
   1465             self.set_units(default)

~\anaconda3\lib\site-packages\matplotlib\category.py in default_units(data, axis)
    105         # the conversion call stack is default_units -> axis_info -> convert
    106         if axis.units is None:
--> 107             axis.set_units(UnitData(data))
    108         else:
    109             axis.units.update(data)

~\anaconda3\lib\site-packages\matplotlib\category.py in __init__(self, data)
    174         self._counter = itertools.count()
    175         if data is not None:
--> 176             self.update(data)
    177 
    178     @staticmethod

~\anaconda3\lib\site-packages\matplotlib\category.py in update(self, data)
    209         for val in OrderedDict.fromkeys(data):
    210             # OrderedDict just iterates over unique values in data.
--> 211             cbook._check_isinstance((str, bytes), value=val)
    212             if convertible:
    213                 # this will only be called so long as convertible is True.

~\anaconda3\lib\site-packages\matplotlib\cbook\__init__.py in _check_isinstance(_types, **kwargs)
   2244     for k, v in kwargs.items():
   2245         if not isinstance(v, types):
-> 2246             raise TypeError(
   2247                 "{!r} must be an instance of {}, not a {}".format(
   2248                     k,

TypeError: 'value' must be an instance of str or bytes, not a float

Still, Jupiter produces some plot which ofc isn't what I am looking for, not to mention that I am obtaining the y1 in terms of place but I do want just to count the number of earthquakes in a year, I just felt that using the 'place' would make the code just to count. Please, help.

Here are the datasets I am working on in case it's useful. Note that they have many more columns but I am not using them as they aren't relevant for this graphic.

okQuakes.csv (test_data1) InjectionWells.csv (test_data2)

Answer 1

Share axis before the creation with sharex Like this

y2 = test_data2['BBLS'].astype(str)

fig=plt.figure()
ax1 = plt.subplot(211)
ax2 = plt.subplot(212, sharex = ax1)

curve1 = ax1.plot (x, y1, label='Number of Earthquakes', color='r')
curve2= ax2.plot (x, y2, label='Number of Barrels Produced', color='b')
plt.plot()
plt.show()