add a label to a plot with seaborn

Question

I did a plot using seaborn, Here is my pltt I would like to add a label for each line. Can you help me please?

import numpy as np
import matplotlib.pylab as plt
import matplotlib.dates as mdates


from matplotlib import style
import pandas as pd
%pylab inline
import seaborn as sns
sns.set_style('darkgrid')
import io
style.use('ggplot')
from datetime import datetime
import time
fig = plt.figure(figsize=(12, 8), dpi=100)
ax1 = fig.add_subplot(111)
x1 = pd.to_datetime(df_no_missing.TIMESTAMP, format="%h:%m")
y1 = df_no_missing.P_ACT_KW
y3 = df_no_missing.P_SOUSCR
yearFmt = mdates.DateFormatter("%H:%M:%S")
ax1.xaxis.set_major_formatter(yearFmt)
ax2 = ax1.twinx()

ax1.plot(x, y1, 'g-')
ax2.plot(x, y2, 'b-')
ax1.plot(x, y3, 'r-')
ax1.set_xlabel('temps')
ax1.set_ylabel('puissance', color='g')
ax2.set_ylabel('dépassement', color='b')
plt.ylim(plt.ylim()[0], 1.0)
plt.show()

Thank you in advance EDIT

I try like you mention :

fig = plt.figure(figsize=(12, 5), dpi=100)
ax1 = fig.add_subplot(111)
x1 = pd.to_datetime(df_no_missing.TIMESTAMP, format="%h:%m")
y1 = df_no_missing.P_ACT_KW
y3 = df_no_missing.P_SOUSCR
yearFmt = mdates.DateFormatter("%H:%M:%S")
ax1.xaxis.set_major_formatter(yearFmt)
ax2 = ax1.twinx()
ax1.plot(x, y1, 'g-', label='label 1')
ax2.plot(x, y2, 'b-', label='label 2')
ax1.plot(x, y3, 'r-', label='label 3')
ax1.plot(0, 0, 'b-', label='label 2')
ax.legend(loc=0)             # add legend in top right corner
ax.grid()                    # show grid lines
ax1.set_xlabel('temps')
ax1.set_ylabel('puissance', color='g')
ax2.set_ylabel('dépassement', color='b')
plt.ylim(plt.ylim()[0], 1.0)
plt.show()

But I got this error :

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
C:\Users\Demonstrator\Anaconda3\lib\site-packages\IPython\core\formatters.py

in call(self, obj) 337 pass 338 else: --> 339 return printer(obj) 340 # Finally look for special method names 341 method = _safe_get_formatter_method(obj, self.print_method)

C:\Users\Demonstrator\Anaconda3\lib\site-packages\IPython\core\pylabtools.py

in (fig) 226 227 if 'png' in formats: --> 228 png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs)) 229 if 'retina' in formats or 'png2x' in formats: 230 png_formatter.for_type(Figure, lambda fig: retina_figure(fig, **kwargs))

C:\Users\Demonstrator\Anaconda3\lib\site-packages\IPython\core\pylabtools.py

in print_figure(fig, fmt, bbox_inches, **kwargs) 117 118 bytes_io = BytesIO() --> 119 fig.canvas.print_figure(bytes_io, **kw) 120 data = bytes_io.getvalue() 121 if fmt == 'svg':

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\backend_bases.py

in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, **kwargs) 2178 orientation=orientation, 2179 dryrun=True, -> 2180 **kwargs) 2181 renderer = self.figure._cachedRenderer 2182 bbox_inches = self.figure.get_tightbbox(renderer)

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\backends\backend_agg.py

in print_png(self, filename_or_obj, *args, **kwargs) 525 526 def print_png(self, filename_or_obj, *args, **kwargs): --> 527 FigureCanvasAgg.draw(self) 528 renderer = self.get_renderer() 529 original_dpi = renderer.dpi

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\backends\backend_agg.py

in draw(self) 472 473 try: --> 474 self.figure.draw(self.renderer) 475 finally: 476 RendererAgg.lock.release()

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\artist.py

in draw_wrapper(artist, renderer, *args, **kwargs) 59 def draw_wrapper(artist, renderer, *args, **kwargs): 60 before(artist, renderer) ---> 61 draw(artist, renderer, *args, **kwargs) 62 after(artist, renderer) 63

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\figure.py

in draw(self, renderer) 1157 dsu.sort(key=itemgetter(0)) 1158 for zorder, a, func, args in dsu: -> 1159 func(*args) 1160 1161 renderer.close_group('figure')

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\artist.py

in draw_wrapper(artist, renderer, *args, **kwargs) 59 def draw_wrapper(artist, renderer, *args, **kwargs): 60 before(artist, renderer) ---> 61 draw(artist, renderer, *args, **kwargs) 62 after(artist, renderer) 63

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\axes\_base.py

in draw(self, renderer, inframe) 2322 2323 for zorder, a in dsu: -> 2324 a.draw(renderer) 2325 2326 renderer.close_group('axes')

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\artist.py

in draw_wrapper(artist, renderer, *args, **kwargs) 59 def draw_wrapper(artist, renderer, *args, **kwargs): 60 before(artist, renderer) ---> 61 draw(artist, renderer, *args, **kwargs) 62 after(artist, renderer) 63

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\axis.py

in draw(self, renderer, *args, **kwargs) 1104 renderer.open_group(name) 1105 -> 1106 ticks_to_draw = self._update_ticks(renderer) 1107 ticklabelBoxes, ticklabelBoxes2 = self._get_tick_bboxes(ticks_to_draw, 1108 renderer)

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\axis.py

in _update_ticks(self, renderer) 947 948 interval = self.get_view_interval() --> 949 tick_tups = [t for t in self.iter_ticks()] 950 if self._smart_bounds: 951 # handle inverted limits

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\axis.py

in (.0) 947 948 interval = self.get_view_interval() --> 949 tick_tups = [t for t in self.iter_ticks()] 950 if self._smart_bounds: 951 # handle inverted limits

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\axis.py

in iter_ticks(self) 890 Iterate through all of the major and minor ticks. 891 """ --> 892 majorLocs = self.major.locator() 893 majorTicks = self.get_major_ticks(len(majorLocs)) 894 self.major.formatter.set_locs(majorLocs)

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\dates.py

in call(self) 1004 def call(self): 1005 'Return the locations of the ticks' -> 1006 self.refresh() 1007 return self._locator() 1008

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\dates.py

in refresh(self) 1024 def refresh(self): 1025 'Refresh internal information based on current limits.' -> 1026 dmin, dmax = self.viewlim_to_dt() 1027 self._locator = self.get_locator(dmin, dmax) 1028

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\dates.py

in viewlim_to_dt(self) 768 vmin, vmax = vmax, vmin 769 --> 770 return num2date(vmin, self.tz), num2date(vmax, self.tz) 771 772 def _get_unit(self):

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\dates.py

in num2date(x, tz) 417 tz = _get_rc_timezone() 418 if not cbook.iterable(x): --> 419 return _from_ordinalf(x, tz) 420 else: 421 x = np.asarray(x)

C:\Users\Demonstrator\Anaconda3\lib\site-packages\matplotlib\dates.py

in _from_ordinalf(x, tz) 269 270 ix = int(x) --> 271 dt = datetime.datetime.fromordinal(ix).replace(tzinfo=UTC) 272 273 remainder = float(x) - ix

ValueError: ordinal must be >= 1





<matplotlib.figure.Figure at 0x1d3b041a400>

 print (df_no_missing.head())

              TIMESTAMP  P_ACT_KW PERIODE_TARIF  P_SOUSCR       SITE  \
145 2015-08-01 23:10:00     248.0            HC     425.0  ST GEREON   
146 2015-08-01 23:20:00     244.0            HC     425.0  ST GEREON   
147 2015-08-01 23:30:00     243.0            HC     425.0  ST GEREON   
148 2015-08-01 23:40:00     238.0            HC     425.0  ST GEREON   
149 2015-08-01 23:50:00     234.0            HC     425.0  ST GEREON   

          TARIF  depassement        date      time  
145  TURPE_HTA5          0.0  2015-08-01  23:10:00  
146  TURPE_HTA5          0.0  2015-08-01  23:20:00  
147  TURPE_HTA5          0.0  2015-08-01  23:30:00  
148  TURPE_HTA5          0.0  2015-08-01  23:40:00  
149  TURPE_HTA5          0.0  2015-08-01  23:50:00

Answer 1

You can specify the label names to each subplot axis and use plt.legend to add the appropriate legends to the center right corner.

fig = sns.plt.figure(figsize=(12, 5), dpi=100)
ax1 = fig.add_subplot(111)
x1 = pd.to_datetime(df_no_missing.TIMESTAMP)
y1 = df_no_missing.P_ACT_KW
y2 = df_no_missing.depassement
y3 = df_no_missing.P_SOUSCR
yearFmt = mdates.DateFormatter("%H:%M:%S")
ax1.xaxis.set_major_formatter(yearFmt)
ax1.plot(x1, y1, 'g-', label='p_act_kw')
ax1.plot(x1, y3, 'r-', label='p_souscr')
ax2 = ax1.twinx()
ax2.plot(x1, y2, 'b-', label='depassement')
h1, l1 = ax1.get_legend_handles_labels()
h2, l2 = ax2.get_legend_handles_labels()
ax1.legend(h1+h2, l1+l2, loc='center right')
ax1.set_xlabel('temps')
ax1.set_ylabel('puissance', color='g')
ax2.set_ylabel('dépassement', color='b')
sns.plt.ylim(plt.ylim()[0], 1.0)
sns.plt.show()