So, im trying to create a bar chart that takes data from a txt file that has 3 rows. The idea is for the bar chart to sum the data from each row, and to graph 3 bars under those numbers in the Y axis, and the name of what does numbers mean in the X axis. Been searching around and i came off with this, but i feel like its really far away from what i really need.
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
arrays = np.loadtxt("D:/uni/txt arkhives/tiempos.txt", dtype=float)
row1 =np.array(arrays[:,0])
row2 =np.array(arrays[:,1])
row3 =np.array(arrays[:,2])
index = pd.MultiIndex.from_arrays(arrays, names=['first', 'second','third'])
df = pd.DataFrame({'A': row1, 'B': row2, 'C': row3}, index=index)
plt.figure()
df.groupby(['row1','row2','row3']).sum().unstack().plot()
plt.grid()
plt.xlabel('x')
plt.ylabel('y')
plt.title('Graph')
plt.legend()
plt.show()
I keep getting this error:
This might what you're looking for:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
##If you do not have headers in your file use:
df = pd.read_table("D:/uni/txt arkhives/tiempos.txt",header=None,names = ['A','B','C'])
##If you do have headers in your file use:
df = pd.read_table("D:/uni/txt arkhives/tiempos.txt")
df['bar'] = 1
dfgroup = df.groupby('bar').sum()
ax = dfgroup [['A','B','C']].plot(kind='bar', title ="Bar Chart", figsize=(15, 10), legend=True, fontsize=12)
ax.set_xlabel("X label", fontsize=12)
ax.set_ylabel("Y Lable", fontsize=12)
plt.show()
Make sure the columns names are A, B, C and it should be good.
Related
Hi I ploted two lines in a figure, the x-axis is the datetime from '2016-04-01' to '2017-03-31', the value showed on the grid line width is one month, namely 30 days, but I want to the grid line of width is 50 days. I mean that I want to show the date value of x-axis is: 2016-04-01, 2016-05-21,2016-07-10,2016-10-18,2016-12-07,2017-01-26,2017-03-17.
T
My code is following:
import seaborn as sn
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
sn.set_style("darkgrid")
xfmt = mdates.DateFormatter('%Y-%m-%d')
fig = plt.figure(figsize=(15,4))
ax = fig.add_subplot(111)
ax.xaxis.set_major_formatter(xfmt)
lst_predictions = list(predictions2)
len_predictions = len(lst_predictions)
plt.plot(lst_index, list(test_y2), label = 'actual')
plt.ylim(ymin=0)
plt.ylim(ymax=140)
plt.xlim([lst_index[0], lst_index[-1]])
plt.plot(lst_index, lst_predictions, label='pred')
plt.legend(loc="upper left")
plt.grid(True)
You can use a DayLocator to control the location of the ticks.
xloc = mdates.DayLocator(interval=50)
ax.xaxis.set_major_locator(xloc)
Usually you would use it in cases where you want to mark the 1st and 15th of each month or so. Since 50 days is more than a month, the location cannot be determined in terms of a month. You may still use the interval argument to space the ticks 50 days appart. However the starting point will be rather arbitrary.
Complete code:
import datetime
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
start_date = datetime.date(2016, 04, 01)
end_date = datetime.date(2017, 07, 01)
date_list = [ start_date + datetime.timedelta(n) for n in range(int ((end_date - start_date).days))]
values = np.cumsum(np.random.rand(len(date_list))-.5)+20
fig, ax = plt.subplots(figsize=(15,4))
ax.plot(date_list, values, label = 'actual')
xloc = mdates.DayLocator(interval=50)
ax.xaxis.set_major_locator(xloc)
xfmt = mdates.DateFormatter('%Y-%m-%d')
ax.xaxis.set_major_formatter(xfmt)
plt.legend(loc="upper left")
plt.grid(True)
plt.show()
I have an array with the shape of (#dim1,#dim2,#channel). I want to reshape it to (#channel, #dim1,#dim2).
The plt.reshape(x, (#channel, #dim1,#dim2)) shows me a wrong image.
If you are using the Cifar10 dataset you could use the following code:
import numpy as np
import matplotlib.pyplot as plt
import cPickle
def unpickle(file):
with open(file, 'rb') as fo:
dict = cPickle.load(fo)
return dict
# Read the data
imageDict = unpickle('cifar-10-batches-py/data_batch_2')
imageArray = imageDict['data']
# Now we reshape
imageArray = np.swapaxes(imageArray.reshape(10000,32,32,3,order='F'), 1, 2)
# Get the labels
labels = ['airplane','automobile','bird','cat','deer','dog','frog','horse','ship','truck']
imageLabels = [labels[i] for i in imageDict['labels']]
# Plot some images
fig, ax = plt.subplots(4,4, figsize=(8,8))
for axIndex in [(i,j) for i in range(4) for j in range(4)]:
index = np.random.randint(0,10000)
ax[axIndex].imshow(imageArray[index], origin='upper')
ax[axIndex].set_title(imageLabels[index])
ax[axIndex].axis('off')
fig.show()
Which gives you:
I am new to Matplotlib. Based on my code in following, I wanted to update the data,title,xlabel,ylabel at same time. However, the title and labels did not been updated, but data did.Someone can give me a solution? That will help me a lot.Thank you.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
def updata(frame_number):
current_index = frame_number % 3
a = [[1,2,3],[4,5,6],[7,8,9]]
idata['position'][:,0] = np.asarray(a[current_index])
idata['position'][:,1] = np.asarray(a[current_index])
scat.set_offsets(idata['position'])
ax.set_xlabel('The Intensity of Image1')
ax.set_ylabel('The Intensity of Image2')
ax.set_title("For Dataset %d" % current_index)
fig = plt.figure(figsize=(5,5))
ax = fig.add_axes([0,0,1,1])
idata = np.zeros(3,dtype=[('position',float,2)])
ax.set_title(label='lets begin',fontdict = {'fontsize':12},loc='center')
scat = ax.scatter(idata['position'][:,0],idata['position'][:,1],s=10,alpha=0.3,edgecolors='none')
animation = FuncAnimation(fig,updata,interval=2000)
plt.show()
Running the code, I see an empty window. The reason is that the axes span the complete figure (fig.add_axes([0,0,1,1])). In order to see the title and labels, you would need to make the axes smaller than the figure, e.g. by
ax = fig.add_subplot(111)
Also, the scale of the axes is not defined, so the animation will happen outside the axes limits. You can use ax.set_xlim and ax.set_ylim to prevent that.
Here is a complete running code:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
def updata(frame_number):
current_index = frame_number % 3
a = [[1,2,3],[4,5,6],[7,8,9]]
idata['position'][:,0] = np.asarray(a[current_index])
idata['position'][:,1] = np.asarray(a[current_index])
scat.set_offsets(idata['position'])
ax.set_xlabel('The Intensity of Image1')
ax.set_ylabel('The Intensity of Image2')
ax.set_title("For Dataset %d" % current_index)
fig = plt.figure(figsize=(5,5))
ax = fig.add_subplot(111)
idata = np.zeros(3,dtype=[('position',float,2)])
ax.set_title(label='lets begin',fontdict = {'fontsize':12},loc='center')
scat = ax.scatter(idata['position'][:,0],idata['position'][:,1],
s=25,alpha=0.9,edgecolors='none')
ax.set_xlim(0,10)
ax.set_ylim(0,10)
animation = FuncAnimation(fig,updata,frames=50,interval=600)
plt.show()
I am trying to extract just the alpha carbon coordinates and plot them in a 3D representation. The top half of the following code works fine, but I can't seem to plot my results.
import re
import glob
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
coord = []
pattern = re.compile('ATOM\s{5,}\d+\s{2}CA\s{2,}\w{3}\s\w\s{2,}\d+\s{6}\d+\.\d+\s\d+\.\d+\s{2}\d+\.\d+', flags=re.S)
for file in glob.glob('file_rank_1.pdb'):
with open(file) as fp:
for result in pattern.findall(fp.read()):
output = result[-22:]
coord = " ".join(output.split())
coord = coord.replace(" ",",")
c = coord.split(',')
print(c)
X,Y,Z = (c)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot_wireframe(X,Y,Z)
ax.set_xlabel('x axis')
ax.set_ylabel('y axis')
ax.set_zlabel('z axis')
plt.show()
My results from running the above looks like...
['72.438', '109.283', '43.980']
['75.664', '110.907', '45.079']
['74.354', '111.094', '48.594']
['73.380', '107.449', '48.722']
['76.614', '106.603', '46.958']
['79.740', '105.625', '48.895']
['82.425', '107.703', '47.318']
['80.088', '110.405', '46.265']
['78.710', '110.389', '49.818']
['82.235', '110.471', '51.200']
['82.841', '113.550', '49.133']
['79.233', '114.754', '49.675']
['78.633', '113.745', '53.295']
['77.041', '117.182', '53.503']
['73.963', '116.530', '51.505']
['73.696', '113.058', '52.933']
TypeError: Cannot cast array data from dtype('float64') to dtype('<U32') according to the rule 'safe'
The above code opens the graph interface, but it remains blank. There is also a full screen of red file messages from the interactive shell that I left off to try to save space in this question.
How can I plot the numbers found in c? Thanks
There are a few things to point out:
1) In the following block, c is a list of strings not floats.
with open(file) as fp:
for result in pattern.findall(fp.read()):
output = result[-22:]
coord = " ".join(output.split())
coord = coord.replace(" ",",")
c = coord.split(',')
print(c)
You can change them using:
[float(i) for i in c]
2) When you set X,Y,Z = (c), that c is only the last item in the loop. So you should append each c within the loop to collect all coordinates.
3) You might want to use numpy for array manipulations.
So hopefully the following will work:
import re
import numpy as np
import glob
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
points = []
pattern = re.compile('ATOM\s{5,}\d+\s{2}CA\s{2,}\w{3}\s\w\s{2,}\d+\s{6}\d+\.\d+\s\d+\.\d+\s{2}\d+\.\d+', flags=re.S)
for file in glob.glob('file_rank_1.pdb'):
with open(file) as fp:
for result in pattern.findall(fp.read()):
output = result[-22:]
coord = " ".join(output.split())
coord = coord.replace(" ",",")
c = coord.split(',')
c = [float(i) for i in c] # change them to float
points.append(c)
print(c)
X,Y,Z=np.array(points).T
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot_wireframe(X,Y,Z)
ax.set_xlabel('x axis')
ax.set_ylabel('y axis')
ax.set_zlabel('z axis')
plt.show()
I have this signal :
from math import*
Fs=8000
f=500
sample=16
a=[0]*sample
for n in range(sample):
a[n]=sin(2*pi*f*n/Fs)
How can I plot a graph (this sine wave)?
and create name of xlabel as 'voltage(V)' and ylabel as 'sample(n)'
What code to do this?
I am so thanksful for help ^_^
Setting the x-axis with np.arange(0, 1, 0.001) gives an array from 0 to 1 in 0.001 increments.
x = np.arange(0, 1, 0.001) returns an array of 1000 points from 0 to 1, and y = np.sin(2*np.pi*x) you will get the sin wave from 0 to 1 sampled 1000 times
I hope this will help:
import matplotlib.pyplot as plt
import numpy as np
Fs = 8000
f = 5
sample = 8000
x = np.arange(sample)
y = np.sin(2 * np.pi * f * x / Fs)
plt.plot(x, y)
plt.xlabel('sample(n)')
plt.ylabel('voltage(V)')
plt.show()
P.S.: For comfortable work you can use The Jupyter Notebook.
import matplotlib.pyplot as plt # For ploting
import numpy as np # to work with numerical data efficiently
fs = 100 # sample rate
f = 2 # the frequency of the signal
x = np.arange(fs) # the points on the x axis for plotting
# compute the value (amplitude) of the sin wave at the for each sample
y = np.sin(2*np.pi*f * (x/fs))
#this instruction can only be used with IPython Notbook.
% matplotlib inline
# showing the exact location of the smaples
plt.stem(x,y, 'r', )
plt.plot(x,y)
import numpy as np
import matplotlib.pyplot as plt
F = 5.e2 # No. of cycles per second, F = 500 Hz
T = 2.e-3 # Time period, T = 2 ms
Fs = 50.e3 # No. of samples per second, Fs = 50 kHz
Ts = 1./Fs # Sampling interval, Ts = 20 us
N = int(T/Ts) # No. of samples for 2 ms, N = 100
t = np.linspace(0, T, N)
signal = np.sin(2*np.pi*F*t)
plt.plot(t, signal)
plt.xlabel('Time (s)')
plt.ylabel('Voltage (V)')
plt.show()
import math
import turtle
ws = turtle.Screen()
ws.bgcolor("lightblue")
fred = turtle.Turtle()
for angle in range(360):
y = math.sin(math.radians(angle))
fred.goto(angle, y * 80)
ws.exitonclick()
The window of usefulness has likely come and gone, but I was working at a similar problem. Here is my attempt at plotting sine using the turtle module.
from turtle import *
from math import *
#init turtle
T=Turtle()
#sample size
T.screen.setworldcoordinates(-1,-1,1,1)
#speed up the turtle
T.speed(-1)
#range of hundredths from -1 to 1
xcoords=map(lambda x: x/100.0,xrange(-100,101))
#setup the origin
T.pu();T.goto(-1,0);T.pd()
#move turtle
for x in xcoords:
T.goto(x,sin(xcoords.index(x)))
A simple way to plot sine wave in python using matplotlib.
import numpy as np
import matplotlib.pyplot as plt
x=np.arange(0,3*np.pi,0.1)
y=np.sin(x)
plt.plot(x,y)
plt.title("SINE WAVE")
plt.show()
import matplotlib.pyplot as plt
import numpy as np
#%matplotlib inline
x=list(range(10))
def fun(k):
return np.sin(k)
y=list(map(fun,x))
plt.plot(x,y,'-.')
#print(x)
#print(y)
plt.show()
This is another option
#!/usr/bin/env python
import numpy as np
import matplotlib
matplotlib.use('TKAgg') #use matplotlib backend TkAgg (optional)
import matplotlib.pyplot as plt
sample_rate = 200 # sampling frequency in Hz (atleast 2 times f)
t = np.linspace(0,5,sample_rate) #time axis
f = 100 #Signal frequency in Hz
sig = np.sin(2*np.pi*f*(t/sample_rate))
plt.plot(t,sig)
plt.xlabel("Time")
plt.ylabel("Amplitude")
plt.tight_layout()
plt.show()
Yet another way to plot the sine wave.
import numpy as np
import matplotlib
matplotlib.use('TKAgg') #use matplotlib backend TKAgg (optional)
import matplotlib.pyplot as plt
t = np.linspace(0.0, 5.0, 50000) # time axis
sig = np.sin(t)
plt.plot(t,sig)
from math import *
Fs = 8000
f = 500
sample = 16
a = [0] * sample
for n in range(sample):
a[n] = sin(2*pi*f*n/Fs)
creating the x coordinates
Sample = [i for i in range(sample)]
importing matplotlib for plotting
import matplotlib.pyplot as plt
adding labels and plotting
plt.xlabel('Voltage(V)')
plt.ylabel('Sample(n)')
plt.plot(Sample, a)
plt.show()