Alignment of the yticks labels of a plt.imshow() figure

Question

I have a pb with the tick's labels alignment of an imshow figure. I would like to center the labels between two Y-ticks but I do not succeed. I know that we can find numerous examples (including in StackOverflow), but I did not find what I was looking for.

import datetime
dateFMT = '%Y-%m-%d %H:%M:%S'
import pandas as pd
import numpy as np

import matplotlib.pyplot as plt
# Fontsize
ftsize = 12

# - Months in French 
tabMois=['Janvier','Fevrier','Mars','Avril','Mai','Juin','Juillet','Aout','Septembre',
 'Octobre','Novembre','Decembre']

# - Nb of Days of Measurements 
NbOfDays = 7.99

# - Generating a DateTimeIndex from January the 1st and during ~8 days
start = datetime.datetime.strptime('2020-01-01 00:00:00', dateFMT)
end = start + datetime.timedelta(days=NbOfDays)
times = pd.date_range(freq='60Min', start=start, end=end)

# - Total number of values
NbOfDates = len (times)

# - Creating the dataframe with random values
df = pd.DataFrame(np.random.randint(0,4,size=(NbOfDates, 1)), 
                  columns=['Temperature'], index=times)

# - Creating 2 columns for referencing dates and hours
date = [d.strftime('%d/%m') for d in df.index]
df['jour'] = date
heure = [d.strftime('%H') for d in df.index]
df['heure'] = heure

# - Creating a new DataFrame (dfPivot) containing the matrix of the previous 
# Dataframe
dfPivot = df.pivot(index='jour', columns='heure', values='Temperature')

# - X Labels for the plot
XTicksLabels = [ str(i)+'h' for i in dfPivot.columns ]

# - Small function to split days and monthes and to translate in French
def splitDate( i ):
    day = i.split('/')[0]
    month = int(i.split('/')[1])
    monthInFrench = tabMois[month-1]
    label = str(day)+' '+monthInFrench
    return label

# - Y Labels for the plot
YTicksLabels = [ splitDate( i ) for i in dfPivot.index ]

# - Plot
fig, ax = plt.subplots()

im = ax.imshow(dfPivot, aspect = 'auto', interpolation='None')

ax.xaxis.set(ticks=np.arange(0.5, len(XTicksLabels)), ticklabels=XTicksLabels)
ax.set_xticklabels(XTicksLabels, rotation=90, ha='right', minor=False)

ax.yaxis.set(ticks=np.arange(0.5, len(YTicksLabels)), ticklabels=YTicksLabels)
ax.set_yticklabels(YTicksLabels, rotation=0, ha='right', va = 'baseline',
                   minor=False, fontsize=ftsize)

ax.tick_params('y', length=10)
fig.colorbar(im)

plt.ylabel('Jours', size=ftsize)
plt.xlabel('Heures', size=ftsize)

plt.tight_layout()
plt.show()

The image produced by the code.

Ed Smith · Accepted Answer · 2020-01-18T19:09:48.457

Based on this answer, you should be able to use,

# Create offset transform by 5 points in y direction
dx = 0/72.; dy = 10/72. 
offset = matplotlib.transforms.ScaledTranslation(dx, dy, fig.dpi_scale_trans)

# apply offset transform to all x ticklabels.
for label in ax.yaxis.get_majorticklabels():
    label.set_transform(label.get_transform() + offset)

As a full example using your data,

import datetime
dateFMT = '%Y-%m-%d %H:%M:%S'
import pandas as pd
import numpy as np
import matplotlib.transforms
import matplotlib.pyplot as plt
# Fontsize
ftsize = 12

# - Months in French 
tabMois=['Janvier','Fevrier','Mars','Avril','Mai','Juin','Juillet','Aout','Septembre','Octobre','Novembre','Decembre']

# - Nb of Days of Measurements 
NbOfDays = 7.99

# - Generating a DateTimeIndex from January the 1st and during ~8 days
start = datetime.datetime.strptime('2020-01-01 00:00:00', dateFMT)
end = start + datetime.timedelta(days=NbOfDays)
times = pd.date_range(freq='60Min', start=start, end=end)

# - Total number of values
NbOfDates = len (times)

# - Creating the dataframe with random values
df = pd.DataFrame(np.random.randint(0,4,size=(NbOfDates, 1)), columns=['Temperature'], index=times)

# - Creating 2 columns for referencing dates and hours
date = [d.strftime('%d/%m') for d in df.index]
df['jour'] = date
heure = [d.strftime('%H') for d in df.index]
df['heure'] = heure

# - Creating a new DataFrame (dfPivot) containing the matrix of the previous 
# Dataframe
dfPivot = df.pivot(index='jour', columns='heure', values='Temperature')

# - X Labels for the plot
XTicksLabels = [ str(i)+'h' for i in dfPivot.columns ]

# - Small function to split days and monthes and to translate in French
def splitDate( i ):
    day = i.split('/')[0]
    month = int(i.split('/')[1])
    monthInFrench = tabMois[month-1]
    label = str(day)+' '+monthInFrench
    return label

# - Y Labels for the plot
YTicksLabels = [ splitDate( i ) for i in dfPivot.index ]

# - Plot
fig, ax = plt.subplots()

im = ax.imshow(dfPivot, aspect = 'auto', interpolation='None')

ax.xaxis.set(ticks=np.arange(0.5, len(XTicksLabels)), ticklabels=XTicksLabels)
ax.set_xticklabels(XTicksLabels, rotation=90, ha='right', minor=False)

ax.yaxis.set(ticks=np.arange(0.5, len(YTicksLabels)), ticklabels=YTicksLabels)
ax.set_yticklabels(YTicksLabels, rotation=0, ha='right', va = 'baseline', minor=False, fontsize=ftsize)

ax.tick_params('y', length=10)
fig.colorbar(im)

plt.ylabel('Jours', size=ftsize)
plt.xlabel('Heures', size=ftsize)

# Create offset transform by 5 points in y direction
dx = 0/72.; dy = 10/72. 
offset = matplotlib.transforms.ScaledTranslation(dx, dy, fig.dpi_scale_trans)

# apply offset transform to all x ticklabels.
for label in ax.yaxis.get_majorticklabels():
    label.set_transform(label.get_transform() + offset)

plt.tight_layout()
plt.show()

which gives,

JohanC · Answer 2 · 2020-01-18T20:22:37.240

Try it this way:

Move the ticklabels a little bit higher (e.g. 0.1).
Use the minor ticks to make the larger seperations between the days, place them at the position where the major ticks were before.
Remove the major tick marks by setting their length to zero.

ax.yaxis.set(ticks=np.arange(0.1, len(YTicksLabels)), ticklabels=YTicksLabels)
ax.set_yticks(ticks=np.arange(0.5, len(YTicksLabels)), minor=True)
ax.tick_params(axis='y', which='minor', length=10)
ax.tick_params(axis='y', which='major', length=0)

Alignment of the yticks labels of a plt.imshow() figure

2 Answers2