Upon running this code:
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns; sns.set()
from sklearn.datasets import make_blobs
X, y_true = make_blobs(n_samples = 300, centers= 4, cluster_std =0.60,random_state = 0)
plt.scatter(X[:,0], X[:,1], s=50)
labels = pairwise_distances_argmin(X, centres)
I am getting a NameError
"name 'pairwise_distances_argmin' is not defined"
What may be the possible reasons for it.
Please note that I am relatively new to this field, elaborated answers are most welcome.
Thanks in advance.
Have searched Stack overflow and unsuccessfully try solutions suggested on these pages:
Weird results of sklearn.metrics.pairwise_distances_argmin_min when computing euclidean distance
NameError: name 'sklearn' is not defined
You wish to use the
pairwise_distances_argmin
function.
You're going to have to import it:
from sklearn.metrics import pairwise_distances_argmin
Related
I just tried to execute this code. but it shows always this error:'f() missing 1 required positional argument:'t'
please can you tell me what should I change?
import numpy as np
def f(y,z,t):
return np.array([2*y+z-t,z+y])
import matplotlib.pyplot as plt
from scipy.integrate import odeint
t=np.linspace(0,2,1000)
sol=odeint(f,[0,1],t)
y,z=sol[:,0],sol[:,1]
plt.plot(t,y,label='y')
plt.plot(t,z,label='z')
plt.show()
Depending on what you are trying to do, you can get around it two ways. To pass in additional arguments other than y and t you need to include them as a constant in the function parameter.
import numpy as np
def f(t,y,z):
return np.array([2*y+z-t,z+y])
import matplotlib.pyplot as plt
from scipy.integrate import odeint
t=np.linspace(0,2,1000)
z = 10.0
sol=odeint(f,[0,1],t, tfirst=True, args=(z, ))
y,z=sol[:,0],sol[:,1]
plt.plot(t,y,label='y')
plt.plot(t,z,label='z')
plt.show()
This will still cause an error. However, if you are also trying to obtain z as result then you should be able to run:
import numpy as np
def f(t,inp):
y, z = inp
return np.array([2*y+z-t,z+y])
import matplotlib.pyplot as plt
from scipy.integrate import odeint
t=np.linspace(0,2,1000)
sol=odeint(f,[0,1],t, tfirst=True)
y,z=sol[:,0],sol[:,1]
plt.plot(t,y,label='y')
plt.plot(t,z,label='z')
plt.show()
This should run without any errors but you may need to double check that this is the result you are expecting.
(The tfirst argument is just for clarity to make ensure the order of arguments provided is correct, you can remove and re-order if you want as well.)
Documentation for odeint function here: https://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.odeint.html
I installed Matplotlib via Anaconda from here: https://anaconda.org/conda-forge/matplotlib
I used the very first command in Anaconda prompt.
But when I tried to plot from python (Spyder) as the following, I get the message:
ModuleNotFoundError: No module named 'matplotlib.plot'
import numpy as np
import matplotlib.plot as plt
x = np.linspace(0, 2*np.pi, 100)
y = np.sin(x)
plt.plot(x,y)
I have installed numpy, pandas and such using the same method and they work well.
How can I fix this?
Thank you so much.
matplotlib.pyplot is a state-based interface to matplotlib. pyplot is mainly intended for interactive plots and simple cases of programmatic plot generation. Therefore, whenever trying to work with graphs and what is commonly known and informally often referred as matplotlib you should import matplotlib.pyplot as plt:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 2*np.pi, 100)
y = np.sin(x)
plt.plot(x,y)
I am trying to scale my data using Python 3
But I keep getting this error: I am out of ideas as to what could be the issue? Please can you assist me guys? I would deeply appreciate your help!
import pandas as pd
import numpy as np
from numpy.random import randn
from pandas import Series, DataFrame
from pandas.plotting import scatter_matrix
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib import rcParams
from pylab import rcParams
import seaborn as sb
import scipy
from scipy import stats
from scipy.stats import pearsonr
from scipy.stats import spearmanr
from scipy.stats import chi2_contingency
import sklearn
from sklearn import preprocessing
from sklearn.preprocessing import scale
mtcars = pd.read_csv('mtcars.csv')
mtcars.columns = ['Car
names','mpg','cyl','disp','hp','drat','wt','qsec','vs','am','gear','carb']
mpg = mtcars['mpg']
#Scale your data
mpg_matrix = mpg.reshape(-1,1)
scaled = preprocessing.MinMaxScaler()
scaled_mpg = scaled.fit_transform(mpg_matrix)
plt.plot(scaled_mpg)
plt.show()
mpg_matrix = mpg.numpy.reshape(-1,1)
tr__
File "C:\Anaconda\lib\site-packages\pandas\core\generic.py", line 5067, in __getattr__
return object.__getattribute__(self, name)
AttributeError: 'Series' object has no attribute 'numpy'
pandas.core.series.Series doesn't have reshape.
Perhaps:
mpg_matrix = mpg.values.reshape(-1,1)
i.e. get the underlying numpy array and reshape that.
Please, I need some help, so I am still in the learning phase of the Python programming for Data Science. I tried plotting a function but I am getting this. Please, what can I do? I am using Python 3. I appreciate your insights, explanations.
import pandas as pd
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib import rcParams
import seaborn as sb
mtcars = pd.read_csv('mtcars.csv')
mtcars.columns = ['Car names','mpg','cyl','disp','hp','drat','wt','qsec','vs','am','gear','carb']
mpg1 = mtcars['mpg']
print(mpg1.plot())
df = mtcars[['mpg','cyl','wt']]
print(df.plot())
When I run to see what the plot is like, this is what I get:
AxesSubplot(0.125,0.11;0.775x0.77)
Please can you explain? How can I see the plot?
Thank you so much
you shouldn't "print" the plot, instead you should just call mpg1.plot() (eventually follpwed by plt.show() if needed)
I am new using python and try to do some plots. I realized, that a plot of a bump function is incorrect. I have no idea how python came to this result.
This is my 'code'
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
import matplotlib.pyplot as plt
class MainBody():
x = np.linspace(0.0001,99.9999,1000)
result = np.exp((-1.0)/(x*(100.0-x)))
plt.plot(x,result)
plt.show()
I got this result
but I should get this
I know that Python is powerful but I think such simple things should work without occuring such errors, where is my mistake?
Thank you
Matthias
Use plt.ylim to set the y-limits. Otherwise, by default, matplotlib will try to show the entire dataset, whose y-limits go roughly from 0 to 1:
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0.0001,99.9999,1000)
result = np.exp((-1.0)/(x*(100.0-x)))
plt.plot(x,result)
plt.ylim(0.9975, 0.9999)
plt.show()