matplotlib axis values are not sorted

Question

I'm using plt.scatter with a set of values, and this is the output I'm getting:

Why am I getting these messy axis, both in the x and in the y? Why are they disordered? I would expect to have an axis starting from 0 and finishing in infinite, and not increasing and decreasing.

This is my code in case you need it:

lines = []
XsR = []
YsR = []
XsL = []
YsL = []
with open('tracking_test.txt') as f:
    lines = f.readlines()
for i in range (len(lines)):
    lines[i] = re.sub(r"[()]", " ", lines[i])
    lines[i] = lines[i].split(',')
    
    if i%2 == 0:
        XsR.append(lines[i][0])
        YsR.append(lines[i][1])
        
    else:
        XsL.append(lines[i][0])
        YsL.append(lines[i][1])   


x = np.array(XsR)
y = np.array(YsR)
plt.scatter(x, y)


x = np.array(XsL)
y = np.array(YsL)
plt.scatter(x, y)

yabs_max = abs(max(ax.get_ylim(), key=abs))
ax.set_ylim(ymin=-yabs_max, ymax=yabs_max)

plt.axhline(y=0.0, color='b', linestyle='-')
plt.axvline(x=0.0, color = 'b', linestyle = '-')

fig = matplotlib.pyplot.gcf()
fig.set_size_inches(12, 9)

plt.show()

The file contains the following:

(140.7, 217.0, 0.0)
(-230.6, 241.4, 0.0)
(0.0, 0.0, 0.0)
(0.0, 0.0, 0.0)
(0.0, 0.0, 0.0)
(0.0, 0.0, 0.0)
(229.6, 119.5, 0.0)
(0.0, 0.0, 0.0)
(232.0, 120.5, 0.0)
(0.0, 0.0, 0.0)
(241.7, 113.7, 0.0)
(-90.6, 172.4, 0.0)
(189.1, 143.0, 0.0)
(-150.3, 145.2, 0.0)
(189.1, 143.0, 0.0)
(-124.7, 182.6, 0.0)
(32.6, 15.3, 0.0)
(-39.5, 109.2, 0.0)
(32.6, 15.3, 0.0)
(-286.6, 33.6, 0.0)
(32.6, 15.3, 0.0)
(-286.6, 33.6, 0.0)
(32.6, 15.3, 0.0)
(-286.6, 33.6, 0.0)

saad_saeed · Accepted Answer · 2021-05-15 10:20:55Z

2

The values are treated as strings. Convert them to float using:

val = float(val)

edited May 15, 2021 at 10:20

answered May 14, 2021 at 20:14

saad_saeed

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Comments

Trenton McKinney · Accepted Answer · 2021-05-16 19:37:25Z

Using the existing code

Specifying the dtype when creating the arrays is the best option using the existing code.
Given that x and y are numpy arrays (e.g. x = np.array(['1', '2', '3']):
- x.astype(float) will also work to convert the type, but is best for when you have access to the array, but not the step creating the array.
- While, float(x) will result in a TypeError.

# convert the lists to arrays and set the dtype
XsR = np.array(XsR, dtype=float)
YsR = np.array(YsR, dtype=float)
XsL = np.array(XsL, dtype=float)
YsL = np.array(YsL, dtype=float)

fig, ax = plt.subplots(figsize=(12, 9))

ax.scatter(XsR, YsR)
ax.scatter(XsL, YsL)

yabs_max = abs(max(ax.get_ylim(), key=abs))
ax.set_ylim(ymin=-yabs_max, ymax=yabs_max)

ax.axhline(y=0.0, color='b', linestyle='-')
ax.axvline(x=0.0, color = 'b', linestyle = '-')

Using `pandas`

Given your data, the most succinct solution is to use pandas to read the data with .read_csv(), but set the separator as something other than a ,.
- This makes pandas read the tuple from the file, into a single column
Use ast.literal_eval to convert the column of string literals into literals, in this case, a tuple of floats
Separate the tuple into separate columns, and then plot the DataFrame with pandas.DataFrame.plot.
This reduces the code from 29 lines to just 11 lines of code.
Using pandas v1.2.4 and matplotlib v3.3.4
- pandas imports matplotlib as a dependency, so using the code below, as shown, it is not required to import matplotlib separately.

import pandas as pd
from ast import literal_eval

# load the data from your file; as shown in the OP, there's no header, so the column will be named 0
# convert the column with ast.literal_eval
df = pd.read_csv('test.csv', sep=';', header=None, converters={0: literal_eval})

# display(df.head(2))
                      0
0   (140.7, 217.0, 0.0)
1  (-230.6, 241.4, 0.0)

# split the column into separate columns
df[['x', 'y', 'z']] = pd.DataFrame(df[0].tolist(), index= df.index)

# display(df.head(2))
                      0      x      y    z
0   (140.7, 217.0, 0.0)  140.7  217.0  0.0
1  (-230.6, 241.4, 0.0) -230.6  241.4  0.0

# split the data by odd and even indices
mask = df.index % 2 == 0
df_sR = df[mask]
df_sL = df[~mask]

# plot the dataframe
ax = df_sR.plot(kind='scatter', x='x', y='y', figsize=(12, 9), c='blue')
df_sL.plot(kind='scatter', x='x', y='y', ax=ax, c='orange')

yabs_max = abs(max(ax.get_ylim(), key=abs))
ax.set_ylim(ymin=-yabs_max, ymax=yabs_max)

ax.axhline(y=0.0, color='b', linestyle='-')
ax.axvline(x=0.0, color = 'b', linestyle = '-')

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matplotlib axis values are not sorted

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Using the existing code

Using `pandas`

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