Python Machine Learning Regression P.1 pandas error - python-3.x

Pycharm screenshot of error message with code above
I don't know what to do about the error. I don't know what it means
also there should print(data.head()) between line 8 & 9.

The error is happening in your data = read.csv() line. Check your working directory, or point explicitly to the file location, using something like:
data = read.csv("C:/Users/user/filename.csv")

Related

Inexplicable value error due to encoding of file in Python

I have a file with saved modelling data like this
1
0
1
Trying to iterate over the file using readlines, which correctly reads the line as zero or one.
Error happens when I cast the string into 1 or 0 Value error my code is this
st1=myfile.readline()
try:
line=float(st1.strip(), base=10)
if line==0: zeros+=1
if line==1 or line==0: ones+=1
except ValueError
I am getting value error in each line. I have no clue what is causing this. I do not want to load whole file into a variable as it is quite large. I tried changing 1 to 100 still error.Though a trivial error, I am unable to fix it.I Searched online forums, stack overflow no help. I don't want Numpy, please don't give some solution using Array operation on NumPy. Can you please help?

Getting error to read edf file using mne-python

I am trying to visualize the EEG data fie which is in .edf file format.For this purpose I am using MNE python.
here is my code
import mne
file = "/home/test.edf"
data = mne.io.read_raw_edf(file,preload=True)
Whenever I run this code below error massage is showing
ValueError: not enough values to unpack (expected 3, got 0)
I could not figure out where is my wrong.
It's not possible to use use the file by specifying the path, event if you add a "~", the directory won't be identified. Better you try to be in the exact directory and try reading the file, i.e go to your home directory and then try specifying the file.
import mne
file = "test.edf"
data = mne.io.read_raw_edf(file)

error uploading csv file on cloud jupyter notebook

I have set up a google cloud account
I want to perform my deep learning much more faster on a jupyter notebook, but
I cannot find a way to read my csv file
I downloaded it with wget from my github account and afterwards I tried
dataset = pd.read_csv('/home/user/.jupyter/SIEMENSTRAIN.csv')
but I get the following error
pandas.parser.CParserError: Error tokenizing data. C error: Expected 2 fields in line 3, saw 12
Why? When I read it on my laptop using my jupyter notebooks, everything runs well
Any suggestions?
I tried the recommended solutions for this error and I got the next warning
/home/user/anaconda3/lib/python3.5/site-packages/ipykernel/main.py:1: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators; you can avoid this warning by specifying engine='python'.
if name == 'main':
When I ran dataset.head() this is what appeared
Any help please?
There are a number of possibilities that could be causing the problem... I would first always make sure that Pandas (pd)'s version is updated and compatible.
The more likely cause is that the CSV itself is not right, so pd.read_csv() is not able to work correctly (thus a Parse Error). This may have something to do with the headers, though I'm not sure what your original CSV file looks like. It's worth playing around with read_csv, for example:
df = pandas.read_csv(fileName, sep='delimiter', header=None)
This tampers with 2 things - the delimiter, and if pd is reading a header from CSV or not.
I go through some pd.read_csv() stuff in my book about Stock Prediction (another cool Machine Learning problem) and Deep Learning, feel free to check it out.
Good Luck!
I tried what you proposed and this is what I got
So, any suggestions?
I suppose that the path is ok, but it just won't be read properly, or am I wrong?

Python3 gdal/ogr open OpenStreetMap data file always returns None

I'm using Python 3 and gdal/ogr module to open/read .osm.pbf data files downloaded from OpenStreetMap. With the method presented in this thread, I could successfully parse open the file a week ago through the following code:
import gdal, ogr
gdal.SetConfigOption('OGR_INTERLEAVED_READING', 'YES')
osm_pbf = ogr.Open('file.osm.pbf')
However, it all happened suddenly that the same method won't work any more to the same .osm.pbf data file. When I try to run osm_pbf = ogr.Open('file.osm.pbf') now, it always returns None. As osm_pbf is always None, it's impossible to parse the data any further.
Does anyone know what's happening here? Your kind help would be greatly appreciated.

pyldavis Unable to view the graph

I am trying to visually depict my topics in python using pyldavis. However i am unable to view the graph. Is it that we have to view the graph in the browser or will it get popped upon execution. Below is my code
import pyLDAvis
import pyLDAvis.gensim as gensimvis
print('Pyldavis ....')
vis_data = gensimvis.prepare(ldamodel, doc_term_matrix, dictionary)
pyLDAvis.display(vis_data)
The program is continuously in execution mode on executing the above commands. Where should I view my graph? Or where it will be stored? Is it integrated only with the Ipython notebook?Kindly guide me through this.
P.S My python version is 3.5.
This not work:
pyLDAvis.display(vis_data)
This will work for you:
pyLDAvis.show(vis_data)
I'm facing the same problem now.
EDIT:
My script looks as follows:
first part:
import pyLDAvis
import pyLDAvis.sklearn
print('start script')
tf_vectorizer = CountVectorizer(strip_accents = 'unicode',stop_words = 'english',lowercase = True,token_pattern = r'\b[a-zA-Z]{3,}\b',max_df = 0.5,min_df = 10)
dtm_tf = tf_vectorizer.fit_transform(docs_raw)
lda_tf = LatentDirichletAllocation(n_topics=20, learning_method='online')
print('fit')
lda_tf.fit(dtm_tf)
second part:
print('prepare')
vis_data = pyLDAvis.sklearn.prepare(lda_tf, dtm_tf, tf_vectorizer)
print('display')
pyLDAvis.display(vis_data)
The problem is in the line "vis_data = (...)".if I run the script, it will print 'prepare' and keep on running after that without printing anything else (so it never reaches the line "print('display')).
Funny thing is, when I just run the whole script it gets stuck on that line, but when I run the first part, got to my console and execute purely the single line "vis_data = pyLDAvis.sklearn.prepare(lda_tf, dtm_tf, tf_vectorizer)" this is executed in a couple of seconds.
As for the graph, I saved it as html ("simple") and use the html file to view the graph.
I ran into the same problem (I use PyCharm as IDE) The problem is that pyLDAvize is developed for Ipython (see the docs, https://media.readthedocs.org/pdf/pyldavis/latest/pyldavis.pdf, page 3).
My fix/workaround:
make a dict of lda_tf, dtm_tf, tf_vectorizer (eg., pyLDAviz_dict)dump the dict to a file (eg mydata_pyLDAviz.pkl)
read the pkl file into notebook (I did get some depreciation info from pyLDAviz, but that had no effect on the end result)
play around with pyLDAviz in notebook
if you're happy with the view, dump it into html
The cause is (most likely) that pyLDAviz expects continuous user interaction (including user-initiated "exit"). However, I rather dump data from a smart IDE and read that into jupyter, than develop/code in jupyter notebook. That's pretty much like going back to before-emacs times.
From experience this approach works quite nicely for other plotting rountines
If you received the module error pyLDA.gensim, then try this one instead:
import pyLdAvis.gensim_models
You get the error because of a new version update.

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