I am currently having an issue with the displayed x labels overlapping on the x axis causing the labels to be illegible.
What I have already tried:
1) The axis has been rotated the ticks to 60 degrees, but some plots still overlap
2) Locator_params has been tried, but it throws an error of " AttributeError: 'List' object has no attribute 'locator_params' "
3)using mdates to access year and month locator has been unsuccessful as well. Following is the example code I tried; from source; Matplotlib date manipulation so that the year tick show up every 12 months
years = mdates.YearLocator()
months = mdates.MonthLocator()
monthsFmt = mdates.DateFormatter('%b-%y')
yearsformat=mdates.DateFormatter('\n\n%Y')
###
ax.xaxis.set_minor_locator(months)
ax.xaxis.set_minor_formatter(monthsFmt)
####
plt.setp(ax.xaxis.get_minorticklabels(), rotation=90)
ax.xaxis.set_major_formatter(years)
ax.xaxis.set_major_formatter(yearsformat)
I believe I may be misunderstanding how to use locator_params & mdates.
Notes:
1) I am using a loop to make ~200 plots that have varying amount of xticks, some with 400+, others with only 15. For this reason, I want to try and set the maximum number of ticks at ~30-40 if possible. However, I am also open to other ideas and suggestions.
Segment of Code:
def plotme(df,string,ref):
for i in range(0,len(df.columns)):
#Scatter plot the active ingredient data.
plotdf=df.iloc[:,i].dropna()
#Store length of df
length=len(plotdf.index)
#Decide on length to cutoff. If index is shorter then 10 datapoints,
exclude it
if length > 10:
#Dataframes setup for Statistics Fucntion
statss=pd.to_numeric(df.iloc[:,i],errors='coerce')
#Last value in the dataframe, aka the most recent
lastvalue=statss[-1]
lastvalue=round(lastvalue,2)
#String Manipulations
#Possibly make a function for this
temp5=str(ref[i])
table = str.maketrans(dict.fromkeys("([)]'"))
temp5=temp5.translate(table)
temp6=temp5.split(',')
#The Iterative Dict split up for accessing
low=float(temp6[1])
low=round(low,2)
high=float(temp6[2])
high=round(high,2)
active=str(temp6[0])
uom=str(temp6[3])
usl=' USL ' + str(high)
lsl=' LSL ' + str(low)
#Call to fucntion for Statistical analysis; a list is returned
#List order; 0==Cp, 1==Cpk, 2==Mean, 3==Standard
stat=statistics(statss,high,low)
mean=stat[2]
standard=stat[3]
cp=stat[0]
cpk=stat[1]
meanstr=str(mean) + ' $\mu$'
title=string + ' ' + active
subtitle='The Cp is ' +str(cp) + ' while the CpK is ' +str(cpk)
ylabel=active + ' (' + uom +')'
plt.figure(0)
#Index is date logged currently, change when index is greater than 100, as overcrowding occurs
ax,=plt.plot(plotdf.index,plotdf, marker='o', linewidth=1, markersize=3)
#ax.locator_params(nbins=4)
#Changing Plot Axis and adding the reference line
plt.title(title)
plt.ylabel(ylabel)
plt.xlabel('Date Logged',fontsize=8)
plt.rc('xtick', labelsize=7)
plt.plot([0,length],[low,low],'r-',lw=3)
plt.plot([0,length],[high,high],'r-',lw=3)
plt.xlim(0,length)
plt.xticks(rotation=60)
#plt.xticks(plt.xticks()[0][1::2],
#plt.xticks()[1][1::2])
#plt.gca().xaxis.set_major_locator(mdates.DayLocator((1,15)))
#plt.gca().xaxis.set_major_formatter(mdates.DateFormatter("%d %b %Y"))
ax.locator_params(axis='x',nbins=40)
plt.plot([0,length],[mean,mean],'g',lw=2,label='$\mu$')
#Add the USL and LSL
#Possibly use Hline subclass instead for efficiency(?)
plt.text((length+0.5),high,usl,fontsize=7,color='red')
plt.text((length+0.5),low,lsl,fontsize=7,color='red')
plt.text((length+0.5),mean,meanstr,fontsize=7,color='green')
#For loop to plot the sigma lines
for i in range(1,5):
minsig=mean-i*standard
adsig=mean+i*standard
cond1=math.isnan(adsig)
cond2=math.isnan(minsig)
####Figure out later####
# if (minsig or adsig)
##Some of the minsig and adsig calculations are nan resulting in an error converting nan to an integer.
if ((cond1==False) and (cond2==False)):
plt.plot([0,length],[minsig,minsig],'k--',lw=1,label='+' + str(i)+' ' + '$\sigma$')
plt.plot([0,length],[adsig,adsig],'k--',lw=1,label='-' + str(i)+ ' ' + '$\sigma$')
plt.text((length+0.1),minsig,'-' + str(i)+' ' + '$\sigma$',fontsize=6)
plt.text((length+0.1),adsig,'+' + str(i)+' ' + '$\sigma$',fontsize=6)
#Save the plots as the name of the title and delete the white space in order to maximize viewability
plt.savefig(title + '.png', bbox_inches='tight',format='png',dpi=800)
plt.show()
plt.figure(1)
plt.rc('xtick', labelsize=8)
sns.distplot(a=plotdf,bins=20,hist_kws=dict(edgecolor='k',linewidth=2))
plt.axvline(low, color='r', linestyle='solid', linewidth=2)
plt.axvline(mean, color='g', linestyle='dashed', linewidth=2)
plt.axvline(high, color='r', linestyle='solid', linewidth=2)
plt.xlabel(ylabel)
plt.title(title + '\n' + subtitle)
plt.savefig(title + ' Normal' +'.png',bbox_inches='tight',format='png',dpi=800)
Example of Issue: The Issue image with overlapping x axis labels
Example of well spaced, ideal case
Thank you everyone for any help in advance.
