I am trying to open a file with the extension .csv in python, however it keeps saying that the file is not found. I am copying the path from the side bar, so I don't believe that's the problem
I have tried to insert / and ./ before the path of the file
And r in front of the file name
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
bkgrnd = pd.read_csv('/Desktop/Sro/Natrium22.csv')
No matter what I've tried, it keeps saying FileNotFoundError
you can import csv if file will be always .csv,
import csv
with open('C:\Users\user\Desktop\Sro\Natrium22.csv') as csv_file:
csv_reader = csv.reader(csv_file, delimiter=',')
line_count = 0
for row in csv_reader:
specifix on windows, it needs normalization of your pathname, maybe thats the issue,
try doing, will surely work,
import os
import pandas as pd
cwd = os.getcwd()
filePath = 'C:/Users/user/Desktop/Sro/Natrium22.csv'
data = pd.read_csv(os.path.normcase(os.path.join(cwd, filePath)))
print(data)
you can try even,
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
bkgrnd = pd.read_csv(r'C:\Users\user\Desktop\Sro\Natrium22.csv')
print(bkgrnd)
Related
import pandas as pd
import numpy as np
import datetime
import yfinance as yf
import matplotlib.pyplot as plt
import warnings
warnings.filterwarnings('ignore')
To use interactive plotting we can also use cufflinks
import cufflinks as cf
To enable offline mode
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
init_notebook_mode(connected=True)
cf.go_offline()
The function downloads daily market data to a pandas DataFrame
def download_daily_data(ticker, start, end):
data = yf.download(ticker, start, end)
return data
The function downloads daily market data to a pandas DataFrame
def download_daily_data(ticker, start, end):
data = yf.download(ticker, start, end)
return data
I'm trying to build my own desktop assistant and got problem with first line. Checking if i got extra space or line but all looks ok, could you please check if anything is wrong?
I did add my script in progress and picture. Thank you all !!
import speech_recognition as sr
import os
import sys
import re
import webbrowser
import smtplib
import requests
import subprocess
from pyowm import OWM
import youtube_dl
import vlc
import urllib
import urllib2
import json
from bs4 import BeautifulSoup as soup
from urllib2 import urlopen
import wikipedia
import random
from time import strftime
def sofiaResponse (audio);
"speaks audio passed as argument"
print(audio)
for line in audio.splitlines():
os.system("say" + audio)
def myCommand ():
"listens for commands"
r = sr.Recognizer()
with sr.Microphone() as source:
print('Say something...')
r.pause_threshold = 1
r.adjust_for_ambient_noise(source, duration=1)
audio = r.listen(source)
try:
command = r.recognize_google(audio).lower()
print('You said: ' + command + '\n')
#loop back to continue listening
except sr.UnknownValueError:
print('Error, help me error')
command = myCommand();
return command
def assistant (command):
"if statements for executing commands"
enter image description here
On line 22, you made a typo :
def sofiaResponse (audio);
should be
def sofiaResponse (audio):
After running this code, i get this exception and i didn't found any place to fix it properly
import networkx as nx
from networkx.algorithms import bipartite
import numpy as np
from pandas import DataFrame, concat
import pandas as pd
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
import ast
import csv
import sys
def plot_degree_dist(G):
in_degrees = G.in_degree()
in_degrees=dict(in_degrees)
in_values = sorted(set(in_degrees.values()))
in_hist = [in_degrees.values().count(x) for x in in_values]
plt.figure()
plt.grid(True)
plt.loglog(in_values, in_hist, 'ro-')
plt.plot(out_values, out_hist, 'bv-')
plt.legend(['In-degree', 'Out-degree'])
plt.xlabel('Degree')
plt.ylabel('Number of nodes')
plt.title('network of places in Cambridge')
#plt.xlim([0, 2*10**2])
I expect to receive a proper graph but all i get is this warning
File "<ipython-input-32-f89b896484d7>", line 2
in_degrees = G.in_degree()
^
IndentationError: expected an indented block
Python relies on proper indentation to identify function blocks. This code should work:
import networkx as nx
from networkx.algorithms import bipartite
import numpy as np
from pandas import DataFrame, concat
import pandas as pd
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
import ast
import csv
import sys
def plot_degree_dist(G):
in_degrees = G.in_degree()
in_degrees=dict(in_degrees)
in_values = sorted(set(in_degrees.values()))
in_hist = [in_degrees.values().count(x) for x in in_values]
plt.figure()
plt.grid(True)
plt.loglog(in_values, in_hist, 'ro-')
plt.plot(out_values, out_hist, 'bv-')
plt.legend(['In-degree', 'Out-degree'])
plt.xlabel('Degree')
plt.ylabel('Number of nodes')
plt.title('network of places in Cambridge')
#plt.xlim([0, 2*10**2])
Basically just indent it by 2 or 4 spaces as per your style requirements.
I want to create a LDA topic model and am using SpaCy to do so, following a tutorial. The error I receive when I try to use spacy is one I cannot find on google, so I'm hoping someone here knows what it's about.
I'm running this code on Anaconda:
import numpy as np
import pandas as pd
import re, nltk, spacy, gensim
# Sklearn
from sklearn.decomposition import LatentDirichletAllocation, TruncatedSVD
from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
from sklearn.model_selection import GridSearchCV
from pprint import pprint
# Plotting tools
import pyLDAvis
import pyLDAvis.sklearn
import matplotlib.pyplot as plt
df = pd.DataFrame(data)
def sent_to_words(sentences):
for sentence in sentences:
yield(gensim.utils.simple_preprocess(str(sentence), deacc=True))
# deacc=True removes punctuations
data_words = list(sent_to_words(data))
print(data_words[:1])
def lemmatization(texts, allowed_postags=['NOUN', 'ADJ', 'VERB', 'ADV']):
"""https://spacy.io/api/annotation"""
texts_out = []
for sent in texts:
doc = nlp(" ".join(sent))
texts_out.append(" ".join([token.lemma_ if token.lemma_ not in ['-PRON-'] else '' for token in doc if token.pos_ in allowed_postags]))
return texts_out
nlp = spacy.load('en', disable=['parser', 'ner'])
# Do lemmatization keeping only Noun, Adj, Verb, Adverb
data_lemmatized = lemmatization(data_words, allowed_postags=['NOUN', 'ADJ', 'VERB', 'ADV'])
print(data_lemmatized[:1])
And I receive the following error:
File "C:\Users\maart\AppData\Local\Continuum\anaconda3\lib\site-packages\_regex_core.py", line 1880, in get_firstset
raise _FirstSetError()
_FirstSetError
The error must occur somewhere after the lemmatization, because the other parts work fine.
Thanks a bunch!
I had this same issue and I was able to resolve it by uninstalling regex (I had the wrong version installed) and then running python -m spacy download en again. This will reinstall the correct version of regex.
I am new to python and as per my thesis work I am trying to convert JSON to csv.I am able to download data in JSON but when I am writing it back using dictionaries it is not converting JSON to CSV with every column.
import pandas as pd
import statsmodels.formula.api as smf
import statsmodels.api as sm
import matplotlib.pyplot as plt
import numpy as np
import requests
from pprint import pprint
import csv
from time import sleep
s1='https://fantasy.premierleague.com/drf/element-summary/'
print s1
players = []
for player_link in range(1,450,1):
link = s1+""+str(player_link)
print link
r = requests.get(link)
print r
player =r.json()
players.append(player)
sleep(1)
with open('C:\Users\dell\Downloads\players_new2.csv', 'w') as f: # Just use 'w' mode in 3.x
w = csv.DictWriter(f,player.keys())
w.writeheader()
for player in players:
w.writerow(player)
I have uploaded the expected output(dec_15_expected.csv) and the program out with file name "player_new_wrong_output.csv"
https://drive.google.com/drive/folders/0BwKYmRU_0K6tZUljd3Q0aG1LT0U?usp=sharing
It will be a great help if some can tell what I am doing wrong.
Converting JSON to CSV is simple with pandas. Try this:
import pandas as pd
df=pd.read_json("input.json")
df.to_csv('output.csv')