Python plt.plot getting unwanted lines

Hi guys, I am trying to plot average usage by month. But somehow on the plot there are unwanted colorful line. The top brown line is correct, but other lines are unwanted. Maybe you know how to get rid of them, and why did they appear? I attached the image of the plot

[SATTI SRIDHAR]

import matplotlib.pyplot as plt

# ... your plotting code goes here ...

# e.g., plt.plot(wavelengths, spectra[0], ...)

# plt.plot(wavelengths, spectra[1], ...)

# ... and so on for all the stars

# Add the legend using the starnames array

plt.legend(starnames)

# ... potentially adjust legend location (optional) ...

# plt.legend(starnames, loc='upper left')

# Display the plot

plt.show()

Answer 1

[adrixas]

I just needed to write all plot function after the for loop not in it. Thanks

Answer 2

[Steven Lord]

Can you show a small segment of your MATLAB code that calls Python and include a small data set with which you can see the unwanted colorful lines?

If you have your data and you want to bin it by month, consider using histogram with the 'DisplayStyle' option set to 'stairs'. I believe that will do what you want or something close to it.

[adrixas]

I attach the dataset file. Here is my entire code:

import matplotlib.pyplot as plt  #
import pandas as pd              #
import numpy as np               #
import scipy.stats as stats      #
from statsmodels.formula.api import ols
from statsmodels.stats.anova import anova_lm

sFile = 'E:/AirQualityUCI.csv'     #
Data = pd.read_table(sFile,';')  #

benzeneref = Data['C6H6(GT)']      #
date= Data['Date']                 #
benzenetit = Data['PT08.S2(NMHC)'] #

mask = ~np.isnan(benzeneref)   #
benzeneref = benzeneref[mask]
benzeneref = np.ma.masked_array(benzeneref, benzeneref == -200) 
benzenetit = benzenetit[mask]
benzenetit = np.ma.masked_array(benzenetit, benzenetit == -200) 
date = date[mask]

month = []  
months = [[]for _ in range(12)] 
day = []    
days = [[]for _ in range(31)]   

for d in date:            
    s = np.int64(d.split('/')) #
    month.append(s[1])         #
    day.append(s[0])           # 

uniqueMonth = np.unique(month)#
uniqueDay = np.unique(day)#

for dd in uniqueDay:               #
    mask1 = day == dd              #
    days[dd-1] = benzeneref[mask1] #

averageref = np.arange(12, dtype=float)  #
averagetit = np.arange(12, dtype=float)#

for mn in uniqueMonth: #
    mask = month == mn #
    print ('month=%d records=%d' %(mn, np.sum(mask))) #
    print ('month=%d mean=%f' %(mn, np.mean(benzeneref[mask])))#
    averageref[mn-1] = np.mean(benzeneref[mask])#
    averagetit[mn-1] = np.mean(benzenetit[mask])#
    months[mn-1] = benzeneref[mask]#

      plt.figure(1)                  #

      plt.figure(2)                  # 

      plt.figure(3)
      plt.plot(uniqueMonth, averagetit)
    #  prog = np.polyfit(uniqueMonth,average1, 1)
    # prog1 = np.polyval(prog,uniqueMonth)
    #  plt.plot(uniqueMonth,prog1)

anova1 = stats.f_oneway(months[0],months[1],months[2],months[3],months[4],months[5],months[6],months[7],months[8],months[9],months[10],months[11])

Answer 3

[SATTI SRIDHAR]

import matplotlib.pyplot as plt

# ... your plotting code goes here ...

# e.g., plt.plot(wavelengths, spectra[0], ...)

# plt.plot(wavelengths, spectra[1], ...)

# ... and so on for all the stars

# Add the legend using the starnames array

plt.legend(starnames)

# ... potentially adjust legend location (optional) ...

# plt.legend(starnames, loc='upper left')

# Display the plot

plt.show()