EDIT - I was being stupid, and trying to plot strings. I converted to int and plotted again fine. Thanks to ImportanceOfBeingErnest for the hint.
I have data from 3 sensors which I want to plot, using matplotlib
Each array is of different length, and I plot them using the following line of code
plt.plot(s_1,'r',s_3,'b',s_4,'g')
plt.show()
This produces the following graph
As you can see, the green trace is not correct, and the y-axis scale is off (these is a 6 after the 21).
I'm really not sure what the problem is here.
When I plot the data individually, they are fine:
It is the last one in this series that is plotted strangely in the graph with all three at once.
To be clear, I don't understand why separately the graphs plot fine, but when the three are printed in one plot the y-axis gets messed up.
Any advice around what the issue with the three-in-one plot is would be great.
Related
I am doing three plots:
Line plot, Boxplot and Histogram.
All these plots don't really need hoverinfo. Also these plots don't really need to plot each point of the data.
Ass you can see the plots are very simple, however, when dealing with huge data (30 million of observations) the html results weights 5 MBs, which is a lot because there are 100 plots more like this.
At the moment I have made some optimizations...
When saving to html I put these parameters:
fig.to_html( include_plotlyjs="cdn", full_html=False)
Which reduces plot size a lot, however is not enough.
I have also tried in the Line plot specifying this parameter line = {"simplify":True} and hoverinfo = "skip". However, file size is almost the same.
Any help/ workaround is appreciated
I am trying to get two different plots as one plot. I will not write down my entire code (is so long), but based on the two small codes below, i get two different time series and I want to put these together in one figure.
My code for the first plot:
plt.figure(figsize=(15,4))
i = plt.plot(july/july.mean(),label='G')
my code for my second plot:
spi3 = pd.read_csv('SPI3.csv',header=0,parse_dates=True)
spi3.plot(y='spi',figsize=(16,4))
Quick dirty fix would be to plot dictionaries at first, only then plot with plt.plot. Also, if you want to plot in the same figure, define figsize only in the first figure you are plotting. (Therefore plt.figure is ommitted completely.)
spi3.plot(y='spi',figsize=(16,4))
plt.plot(july/july.mean(),label='G')
I am plotting a distribution of variables that are outputs from two different versions of a program. They look very similar (this is great because they should!) and I am showing their ratio in the same figure but on a different axis. My goal is to show the ratio as a scatter plot but with a horizontal line at y=1.0 to show 100% agreement. The issue I am having is even if I plot the line first and then the scatter, my scatter points still show underneath the line plot. (Please see the image linked below.) You can see the scatter in black underneath the line plot in red, even though I call the plot function first. Any recommendations? Thank you!
Distribution of two variables with ratio plot underneath
I am plotting some data from a CSV. I recently edited the date range of the CSV file but the values are the same. Before, the data was being plotted simulatiously with 2 other data sets, and the legend had only one entry for this data set. After editing the CSV file, the legend now displays the label 3 times but overall graphs the data correctly. I have tried removing the other two data sets from the plot, using numpoints=1, and ensuring nothing is in a for loop (which none of this code uses one). Additionally, I made sure there wasn't 3 versions of the data saved in the same directory. Any suggestions on why this is happening and how to fix it? I'm including my plotting code in case something is in it that is wrong.
plt.plot(date_range,ice_extent1,color='red',label='MASIE')
plt.xlabel("Date (yyyy/mm)")
plt.ylabel("Sea Ice Extent (10^6 km^2)")
plt.title("Sea Ice Extent")`
plt.legend()
`I am trying to reproduce the attached figure step by step. My problem was that how can i plot colorbar in above figure by my data. My data is a cosmological data and it has 7 columns totally with many raw. My main goal is reproducing the present figure step by step. You can see that there are three different plots which are interpolated each other. Firstly, i tried to plot small colorful lines in the body of figure by using two columns of data. I did it by scatter plots and then i needed to reproduce the colorbar part of figure. But, it was not possible at the first attempt. Because, the colorbar points was not a part of data. Then, i obtained the values of colorbar by some calculations and added them as additional columns to data. Now, i could you the simple colorbar function to do colorbar part. And i got it. For the next step, i need to turn small curved lines to dark solid lines.
How can I do plots in matplotlib?
import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
data1 = np.loadtxt("bei_predic.txt", unpack=True)
B = np.log10(data1[3]/(4.*(data1[2])))
R = np.vstack((data1,B))
R = np.transpose(R)
D = R[~np.isnan(R).any(axis=1)]
A = plt.scatter(D[:,3],D[:,2], c=D[:,8])
cbar= plt.colorbar()
cbar.set_label("file", labelpad=+1)
plt.show()
If you could start off by telling us a little bit about the data that you are using that would be great. In order to plot the figure that you want, we must first load the data into some variables. Have you managed to do this?
Check out this example in which the author plots multicolored lines for some guidance.