How to remove repeating and empty or unmarked values on subplot of x-axis - python-3.x

Question

I'm developing a set of graphs to paint some Pandas DataFrame values. For that I'm using various pandas, numpy and matplotlib modules and functions using the following code:
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.ticker as ticker
data = {'Name': ['immoControlCmd', 'BrkTerrMde', 'GlblClkYr', 'HsaStat', 'TesterPhysicalResGWM', 'FapLc','FirstRowBuckleDriver', 'GlblClkDay'],
'Value': [0, 5, 0, 4, 0, 1, 1, 1],
'Id_Par': [0, 0, 3, 3, 3, 3, 0, 0]
}
signals_df = pd.DataFrame(data)
def plot_signals(signals_df):
# Count signals by par
signals_df['Count'] = signals_df.groupby('Id_Par').cumcount().add(1).mask(signals_df['Id_Par'].eq(0), 0)
# Subtract Par values from the index column
signals_df['Sub'] = signals_df.index - signals_df['Count']
id_par_prev = signals_df['Id_Par'].unique()
id_par = np.delete(id_par_prev, 0)
signals_df['Prev'] = [1 if x in id_par else 0 for x in signals_df['Id_Par']]
signals_df['Final'] = signals_df['Prev'] + signals_df['Sub']
# signals_df['Finall'] = signals_df['Final'].unique()
# print(signals_df['Finall'])
# Convert and set Subtract to index
signals_df.set_index('Final', inplace=True)
# pos_x = len(signals_df.index.unique()) - 1
# print(pos_x)
# Get individual names and variables for the chart
names_list = [name for name in signals_df['Name'].unique()]
num_names_list = len(names_list)
num_axis_x = len(signals_df["Name"])
# Creation Graphics
fig, ax = plt.subplots(nrows=num_names_list, figsize=(10, 10), sharex=True)
plt.xticks(np.arange(0, num_axis_x), color='SteelBlue', fontweight='bold')
for pos, (a_, name) in enumerate(zip(ax, names_list)):
# Get data
data = signals_df[signals_df["Name"] == name]["Value"]
# Get values axis-x and axis-y
x_ = np.hstack([-1, data.index.values, len(signals_df) - 1])
# print(data.index.values)
y_ = np.hstack([0, data.values, data.iloc[-1]])
# Plotting the data by position
ax[pos].plot(x_, y_, drawstyle='steps-post', marker='*', markersize=8, color='k', linewidth=2)
ax[pos].set_ylabel(name, fontsize=8, fontweight='bold', color='SteelBlue', rotation=30, labelpad=35)
ax[pos].yaxis.set_major_formatter(ticker.FormatStrFormatter('%0.1f'))
ax[pos].yaxis.set_tick_params(labelsize=6)
ax[pos].grid(alpha=0.4, color='SteelBlue')
plt.show()
plot_signals(signals_df)
What I want is to remove the points or positions of the x-axis where nothing is painted or they are not marked on the graph, but leave the values ​​and names as in the image at the end; Seen from Pandas it would be the "Final" column that, before painting the subplots, assigned it as an index and it is where some of the values ​​in this column are repeated; would be to remove the values ​​enclosed in the red box from the graph, but leave the values ​​and names as in the image at the end:
Name Value Id_Par Count Sub Prev
Final
0 immoControlCmd 0 0 0 0 0
1 BrkTerrMde 5 0 0 1 0
2 GlblClkYr 0 3 1 1 1
2 HsaStat 4 3 2 1 1
2 TesterPhysicalResGWM 0 3 3 1 1
2 FapLc 1 3 4 1 1
6 FirstRowBuckleDriver 1 0 0 6 0
7 GlblClkDay 1 0 0 7 0
I've been trying to bring the unique values ​​of the last column, which would be the value that the x-axis should be, but since the dataframe is of another size or dimension, I get an error: ValueError: Length of values ​​(5) does not match length of index (8), and then I have to resize my chart, but in this case I don't understand how to do it:
signals_df['Final'] = signals_df['Prev'] + signals_df['Sub']
signals_df['Finall'] = signals_df['Final'].unique()
print(signals_df['Finall'])
I've also tried to bring the size of the unique index, previously assigned to apply a subtraction to data.index.values ​​of the variable x_, but it does not bring me what I want because it is gathering all the values ​​and subtracting them in bulk and not separately , as is data.index.values:
signals_df.set_index('Final', inplace=True)
pos_x = len(signals_df.index.unique()) - 1
...
..
.
x_ = np.hstack([-1, data.index.values-pos-x, len(signals_df) - 1])
Is there a Pandas and/or Matplotlib function that allows me? or Could someone give me a suggestion that will help me better understand how to do it? what I expect to achieve would be the plot below:
I really appreciate your help, any comments help.
I've Python version: 3.6.5, Pandas version: 1.1.5 and Matplotlib version: 3.3.2

Answer 1

One possible way to do this is if you make your x-axis values into strings, which means that matplotlib will make a "categorical" plot. See examples of that here.
For your case, because you have subplots which would have different values, and they are not always in the right order, we need to do a bit of trickery first to make sure the ticks appear in the correct order. For that, we can use the approach from this answer, where they plot something that uses all of the x values in the correct order, and then remove it.
To gather all the xtick values together, you can do something like this, where you create a list of the values, reduce it to the unique values using a set, then sort those values, and convert to strings using a list comprehension and str():
# First make a list of all the xticks we want
xvals = [-1,]
for name in names_list:
xvals.append(signals_df[signals_df["Name"] == name]["Value"].index.values[0])
xvals.append(len(signals_df)-1)
# Reduce to only unique values, sorted, and then convert to strings
xvals = [str(i) for i in sorted(set(xvals))]
Once you have those, you can make a dummy plot, and then remove it, like so (this is to fix the tick positions in the correct order). NOTE that this needs to be inside your plotting loop for matplotlib versions 3.3.4 and earlier:
# To get the ticks in the right order on all subplots, we need to make
# a dummy plot here and then remove it
dummy, = ax[0].plot(xvals, np.zeros_like(xvals))
dummy.remove()
Finally, when you actually plot the real data inside the loop, you just need to convert x_ to strings as you plot them:
ax[pos].plot(x_.astype('str'), y_, drawstyle='steps-post', marker='*', markersize=8, color='k', linewidth=2)
Note the only other change I made was to not explicitly set the xtick positions (which you did, with plt.xticks), but you can still use that command to set the font colour and weight
plt.xticks(color='SteelBlue', fontweight='bold')
And this is the output:
For completeness, here I have put it all together in your script:
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
import matplotlib.ticker as ticker
import matplotlib
print(matplotlib.__version__)
data = {'Name': ['immoControlCmd', 'BrkTerrMde', 'GlblClkYr', 'HsaStat', 'TesterPhysicalResGWM', 'FapLc',
'FirstRowBuckleDriver', 'GlblClkDay'],
'Value': [0, 5, 0, 4, 0, 1, 1, 1],
'Id_Par': [0, 0, 3, 3, 3, 3, 0, 0]
}
signals_df = pd.DataFrame(data)
def plot_signals(signals_df):
# Count signals by par
signals_df['Count'] = signals_df.groupby('Id_Par').cumcount().add(1).mask(signals_df['Id_Par'].eq(0), 0)
# Subtract Par values from the index column
signals_df['Sub'] = signals_df.index - signals_df['Count']
id_par_prev = signals_df['Id_Par'].unique()
id_par = np.delete(id_par_prev, 0)
signals_df['Prev'] = [1 if x in id_par else 0 for x in signals_df['Id_Par']]
signals_df['Final'] = signals_df['Prev'] + signals_df['Sub']
# signals_df['Finall'] = signals_df['Final'].unique()
# print(signals_df['Finall'])
# Convert and set Subtract to index
signals_df.set_index('Final', inplace=True)
# pos_x = len(signals_df.index.unique()) - 1
# print(pos_x)
# Get individual names and variables for the chart
names_list = [name for name in signals_df['Name'].unique()]
num_names_list = len(names_list)
num_axis_x = len(signals_df["Name"])
# Creation Graphics
fig, ax = plt.subplots(nrows=num_names_list, figsize=(10, 10), sharex=True)
# No longer any need to define where the ticks go, but still set the colour and weight here
plt.xticks(color='SteelBlue', fontweight='bold')
# First make a list of all the xticks we want
xvals = [-1, ]
for name in names_list:
xvals.append(signals_df[signals_df["Name"] == name]["Value"].index.values[0])
xvals.append(len(signals_df) - 1)
# Reduce to only unique values, sorted, and then convert to strings
xvals = [str(i) for i in sorted(set(xvals))]
for pos, (a_, name) in enumerate(zip(ax, names_list)):
# To get the ticks in the right order on all subplots,
# we need to make a dummy plot here and then remove it
dummy, = ax[pos].plot(xvals, np.zeros_like(xvals))
dummy.remove()
# Get data
data = signals_df[signals_df["Name"] == name]["Value"]
# Get values axis-x and axis-y
x_ = np.hstack([-1, data.index.values, len(signals_df) - 1])
y_ = np.hstack([0, data.values, data.iloc[-1]])
# Plotting the data by position
# NOTE: here we convert x_ to strings as we plot, to make sure they are plotted as catagorical values
ax[pos].plot(x_.astype('str'), y_, drawstyle='steps-post', marker='*', markersize=8, color='k', linewidth=2)
ax[pos].set_ylabel(name, fontsize=8, fontweight='bold', color='SteelBlue', rotation=30, labelpad=35)
ax[pos].yaxis.set_major_formatter(ticker.FormatStrFormatter('%0.1f'))
ax[pos].yaxis.set_tick_params(labelsize=6)
ax[pos].grid(alpha=0.4, color='SteelBlue')
plt.show()
plot_signals(signals_df)