Python

WindowsError: [Error 5] Access is denied: Anaconda Python Pip Installs and Upgrade

Bydatapandasadmin January 6, 2017January 6, 2017

I was trying to run a pip install ( pip install scikit-learn) and I encountered this error:

C:\Users\adaba>pip install -U scikit-learn

Collecting scikit-learn

Using cached scikit_learn-0.18.1-cp27-cp27m-win_amd64.whl

Installing collected packages: scikit-learn

Found existing installation: scikit-learn 0.17.1

DEPRECATION: Uninstalling a distutils installed project (scikit-learn) has been deprecated and will be removed in a future version. This is due to the fact that uninstalling a distutils project will only partially uninstall the project.

Uninstalling scikit-learn-0.17.1:

Exception:

Traceback (most recent call last):

File "C:\Program Files\Anaconda2\lib\site-packages\pip\basecommand.py", line 215, in main

status = self.run(options, args)

File "C:\Program Files\Anaconda2\lib\site-packages\pip\commands\install.py", line 317, in run

prefix=options.prefix_path,

File "C:\Program Files\Anaconda2\lib\site-packages\pip\req\req_set.py", line 736, in install

requirement.uninstall(auto_confirm=True)

File "C:\Program Files\Anaconda2\lib\site-packages\pip\req\req_install.py", line 742, in uninstall

paths_to_remove.remove(auto_confirm)

File "C:\Program Files\Anaconda2\lib\site-packages\pip\req\req_uninstall.py", line 115, in remove

renames(path, new_path)

File "C:\Program Files\Anaconda2\lib\site-packages\pip\utils\__init__.py", line 267, in renames

shutil.move(old, new)

File "C:\Program Files\Anaconda2\lib\shutil.py", line 303, in move

os.unlink(src)

WindowsError: [Error 5] Access is denied: 'c:\\program files\\anaconda2\\lib\\site-packages\\scikit_learn-0.17.1-py2.7.egg-info'

This is the bit we are interested in ”

1	WindowsError: [Error 5] Access is denied: 'c:\\program files\\anaconda2\\lib\\site-packages\\scikit_learn-0.17.1-py2.7.egg-info'

”

if you look at the error it states “WindowsError”

Hence the Access Denied error is due to not having the right level of privileges to carry out the installs or upgrade.

SOLUTION

Open Command Prompt as Administrator (with Administrator rights)

Now run your pip installs and the windowsError should disappear and installation go through

Microsoft Windows [Version 10.0.14393]

C:\WINDOWS\system32>cd\

C:\>Python

Python 2.7.12 |Anaconda 4.2.0 (64-bit)| (default, Jun 29 2016, 11:07:13) [MSC v.1500 64 bit (AMD64)] on win32

Type "help", "copyright", "credits" or "license" for more information.

Anaconda is brought to you by Continuum Analytics.

Please check out: http://continuum.io/thanks and https://anaconda.org

Could not open PYTHONSTARTUP

IOError: [Errno 2] No such file or directory: 'C:\\Users\\adaba\\Anaconda3\\envs\\gl-env\\Lib\\site-packages\\spyderlib\\scientific_startup.py'

>>>

C:\>pip install -U scikit-learn

Collecting scikit-learn

Using cached scikit_learn-0.18.1-cp27-cp27m-win_amd64.whl

Installing collected packages: scikit-learn

Found existing installation: scikit-learn 0.17.1

Uninstalling scikit-learn-0.17.1:

Successfully uninstalled scikit-learn-0.17.1

Successfully installed scikit-learn-0.18.1

Hope this helps you 🙂

Want more information like this?

Python

Crab Recommender System – Framework in Python Example and installation Problem Fix
Bydatapandasadmin August 21, 2016November 14, 2016

This is just to show that the import errors which were encountered during the installation of Crab, a Recommender Framework in Python worked fine with the fixes I earlier outlined. These were the errors and how they were fixed: ImportError: No module named ‘scikits ImportError: No module named learn.base The code below is the…

Read More Crab Recommender System – Framework in Python Example and installation Problem Fix

Python

Array Transposition – Numpy Python Data Analysis

Bydatapandasadmin August 21, 2016October 23, 2016

Welcome Guys, We will be looking at Array transposition in this quick notes. This is part of lectures on Learning Python for Data Analysis and Visualization by Jose Portilla on Udemy. In [1]:

1	import numpy as np

In [2]:

1 2	arr = np.arange(50) arr

Out[2]:

array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,

17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,

34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49])

In [17]:

1	arr.reshape((10,5))

Out[17]:

array([[ 0, 1, 2, 3, 4],

[ 5, 6, 7, 8, 9],

[10, 11, 12, 13, 14],

[15, 16, 17, 18, 19],

[20, 21, 22, 23, 24],

[25, 26, 27, 28, 29],

[30, 31, 32, 33, 34],

[35, 36, 37, 38, 39],

[40, 41, 42, 43, 44],

[45, 46, 47, 48, 49]])

In [10]:

arr.T

Out[10]:

array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,

17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,

34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49])

In [11]:

1	np.dot(arr.T, arr)

Out[11]:

40425

In [23]:

1	arr3d = np.arange(50).reshape((5,5,12))

---------------------------------------------------------------------------

ValueError Traceback (most recent call last)

<ipython-input-23-8908d625ec66> in <module>()

----> 1 arr3d = np.arange(50).reshape((5,5,12))

ValueError: total size of new array must be unchanged

…

Data Science | Excel | Python | R - Programming | Resources | SQL

Java Python R SQL Excel Compared Similarities For Data Science and Data Analytics – The Basics
Bydatapandasadmin June 9, 2017June 9, 2017

If you have ever worked with Java, Python, R, SQL, Excel and other Languages on a varied Data Science or Data Analytics projects, you will realise that all these languages have similar syntaxes, or at least, can achieve the same objective with very similar codes. Below is a comparison and similarities of these various tools…

Read More Java Python R SQL Excel Compared Similarities For Data Science and Data Analytics – The Basics

Python

Matplotlib Pyplot Plt Python Pandas Data Visualization Plotting

Bydatapandasadmin August 26, 2016October 23, 2016

This is some quick notes about graphing or plotting graphs with Matplotlib in Python. Credits to sentdex. You can check him out on Youtube.

import matplotlib.pyplot as plt

%matplotlib inline

# simple syntax is matplotlib plots as plt.plot(x, y)

plt.plot([1,2,3], [5,6,7])

plt.show()

In [4]:

# plotting with variables and basic labelling of our plot

x = [1,2,3]

y = [5,6,7]

##adding a legend to the plot

#add another line vectors first

x2 = [4,6,8]

y2= [10,14,18]

plt.plot(x, y, label='First Line') # you have to give the plots a label before you can call the legends on them

plt.plot(x2, y2, label='Second Line')

plt.xlabel('Plot number')

plt.ylabel('Important var')

plt.title('Plotting\nNice Graph') #\nGives you a sub title

plt.legend() #call the legend

plt.show()

In [10]:

#plotting barcharts and histograms

x3 = [2,4,6,8,10]

y3 = [3,5,7,9,11]

#second set of bars

x4 = [1,3,5,7,9]

y4 = [2,6,6,12,4]

#plot barchart

plt.bar(x3, y3, label='Bar1', color='r')

plt.bar(x4,y4, label='Bar2', color ='c')

plt.xlabel('x3')

plt.ylabel('y3')

plt.title('Bar Chart')

plt.legend()

plt.show()

In [14]:

#plotting histogram.

population_dist = [24,45,5,6,42,65,34,75,75,34,75,7,24,26,87,98,98,67,86, 65,63, 87,98,76,53,35]

#ids = [x for x in range(len(population_dist))] for bar chart plotting

#plot barchart

#plt.bar(ids, population_dist, label='hist')

#histogram works with bins so we will have to create bin 'containers' for our distribution

bins = [10,20,30,40,50,60,70,80,90,100]

plt.hist(population_dist, bins, histtype='bar', rwidth=0.5)

plt.xlabel('x3')

plt.ylabel('y3')

plt.title('Histogram')

plt.legend()

plt.show()

In [20]:

## scatter plot.

#basic skeletion

x = [1,2,3,4,5,6,7,8,9]

y = [4,5,8,3,6,9,5,4,8]

plt.scatter(x,y, label='ScatterShow', color='c', marker='^' , s=60) # s = size of the marker

plt.xlabel('x3')

plt.ylabel('y3')

plt.title('Scatter')

plt.legend()

plt.show()

In [23]:

#stacked plot

days = [1, 2, 3, 4, 5]

sleeping = [6,8,7,3,8]

eating = [6,9,7,3,6]

working = [9,8,5,7,8]

#working around legends for stackplots

plt.plot([],[], color='red', label='eating', linewidth=2)

plt.plot([],[], color='blue', label='sleeping', linewidth=2)

plt.plot([],[], color='yellow', label='working', linewidth=2)

plt.stackplot(days, eating, sleeping, working, color=['red','blue','yellow'])

plt.xlabel('x3')

plt.ylabel('y3')

plt.title('Stacked Plot')

plt.legend()

plt.show()

In [30]:

#pie charts

days = [1, 2, 3, 4, 5]

sleeping = [6,8,7,3,8]

eating = [6,9,7,3,6]

working = [9,8,5,7,8]

slices = [2,4,6,8,1]

colors = ['red','blue','green','brown','pink']

activities = ['sleeping','eating','working','dancing','travelling']

plt.pie(slices, labels=activities, colors=colors, startangle=90, shadow=True, explode=(0,0.1,0,0,0), autopct='%1.1f%%')

Out[30]:

([<matplotlib.patches.Wedge at 0x814e588>,

<matplotlib.patches.Wedge at 0x7fb7080>,

<matplotlib.patches.Wedge at 0x96f9ba8>,

<matplotlib.patches.Wedge at 0x82853c8>,

<matplotlib.patches.Wedge at 0x785a080>],

[<matplotlib.text.Text at 0x82ac4a8>,

<matplotlib.text.Text at 0x96f9438>,

<matplotlib.text.Text at 0x8026390>,

<matplotlib.text.Text at 0x94ac400>,

<matplotlib.text.Text at 0x785ada0>],

[<matplotlib.text.Text at 0x7fb7fd0>,

<matplotlib.text.Text at 0x96f97b8>,

<matplotlib.text.Text at 0x8285f98>,

<matplotlib.text.Text at 0x94aca58>,

<matplotlib.text.Text at 0x65bf860>])

In [48]:

#modifying the matplotlib

#plotting barchart.

x3 = [2,4,6,8,10]

y3 = [3,5,7,9,11]

#second set of bars

x4 = [1,3,5,7,9]

y4 = [2,6,6,12,4]

fig = plt.figure(facecolor='#f0f0f0') #set facecolour or background colour which will be maintained once we save our graph

ax1 = plt.subplot2grid((1,1),(0,0))

#tilt the xlabels

for labels in ax1.xaxis.get_ticklabels():

labels.set_rotation(45)

#plot barchart

ax1.bar(x3, y3, label='Bar1', color='r')

ax1.bar(x4,y4, label='Bar2', color ='c')

ax1.grid(True) #add a grid

plt.xlabel('x3')

plt.ylabel('y3')

plt.title('Bar Chart')

plt.legend()

#customise the legend

leg = ax1.legend(loc=2,ncol=6, prop={'size':10})

leg.get_frame().set_alpha(0.4)

##define spacing around the ticks and labels

plt.subplots_adjust(left = 0.09, bottom=0.20, right=0.94, top= 0.93, wspace = 0.2, hspace = 0)

plt.show()

#lets save the graph

fig.savefig('matplotlib.png', facecolor=fig.get_facecolor())

Want more information like this? Email People…

Data Science | Python | R - Programming

Run Your Python and R Codes Online For Your Data Science and Machine Learning Projects Mini Projects For Free
ByBernard Adabankah December 28, 2018December 28, 2018

Sometimes, you would want to easily access and run your Python and R codes wherever you find yourself in the world once you have internet access. This is really handy when you have a mini-project you are working on , or you are going through an online tutorial, or you are trying to teach or…

Read More Run Your Python and R Codes Online For Your Data Science and Machine Learning Projects Mini Projects For Free
Data Science | Python

Pandas DataFrame and Series Alignment Python Notes
Bydatapandasadmin August 12, 2016October 23, 2016

This week we have a look at Data Alignment in Python In [1]:

Default

1
2
3

import numpy as np
import pandas as pd
from pandas import Series, DataFrame

In [2]:

Default

1
2
3

#create series
ser1 = Series([0,1,3], index=['A','B','C'])
ser1

Out[2]:

Default

1
2
3
4

A 0
B 1
C 3
dtype: int64

In [3]:

Default

1
2

ser2 = Series([3,4,5,6], index=['A','B','C','D'])
ser2

Out[3]:

Default

1
2
3
4
5

A 3
B 4
C 5
D 6
dtype: int64

In [4]:

Default

1
2

#adding two series which have different lenghts
ser1 + ser2

Out[4]:

Default

1
2
3
4
5

A 3.0
B 5.0
C 8.0
D NaN
dtype: float64

In [6]:

Default

1
2
3
4

#lets try and add dataframes
#create dataframe
dframe = DataFrame(np.arange(4).reshape((2,2)), columns=list('AB'), index=['LA','GA'])
dframe

Out[6]: A B LA 0 1 GA 2 3 In [10]:

Default

1
2
3

#create a second dataframe
dframe2 = DataFrame(np.arange(9).reshape((3,3)), columns=list('ABC'), index=['LA','NYC','GA'])
dframe2

Out[10]: A B C LA 0 1 2 NYC 3 4…

Read More Pandas DataFrame and Series Alignment Python Notes

2 Comments

Aneesh says:

August 22, 2017 at 4:20 pm

I am running as administrator. Still I have this error.

File “c:\python27\lib\site-packages\pip\_vendor\retrying.py”, line 200, in call
attempt = Attempt(fn(*args, **kwargs), attempt_number, False)
File “c:\python27\lib\site-packages\pip\utils\__init__.py”, line 102, in rmtree
onerror=rmtree_errorhandler)
File “c:\python27\lib\shutil.py”, line 252, in rmtree
onerror(os.remove, fullname, sys.exc_info())
File “c:\python27\lib\site-packages\pip\utils\__init__.py”, line 110, in rmtree_errorhandler
if os.stat(path).st_mode & stat.S_IREAD:
WindowsError: [Error 5] Access is denied: ‘c:\\users\\XXXX\\appdata\\local\\temp\\pip-vawmxw-unpack\\pytz-2017.2-py2.py3-none-any.whl’

Reply
1. datapandasadmin says:
  
  August 22, 2017 at 5:00 pm
  
  Hi Aneesh,
  Can you check that the file is not being accessed or opened by any other program.
  Sometimes the file might be accessed by another program without you realising. A simple case of restart and running command prompt as an administrator might help solve it
  
  Reply

WindowsError: [Error 5] Access is denied: Anaconda Python Pip Installs and Upgrade

Crab Recommender System – Framework in Python Example and installation Problem Fix

Array Transposition – Numpy Python Data Analysis

Java Python R SQL Excel Compared Similarities For Data Science and Data Analytics – The Basics

Matplotlib Pyplot Plt Python Pandas Data Visualization Plotting

Run Your Python and R Codes Online For Your Data Science and Machine Learning Projects Mini Projects For Free

Pandas DataFrame and Series Alignment Python Notes

2 Comments

Leave a Reply Cancel reply

DataPandas LTS

EXPLORE DataPandas

ImportAnt link

GET IN TOUCH

© 2026 DataPandas

People Who Read The Above Post Also Read This:

Similar Posts

2 Comments

Leave a Reply Cancel reply

DataPandas LTS

EXPLORE DataPandas

ImportAnt link

GET IN TOUCH

© 2026 DataPandas