I am pretty new to Python (using Python3) and read Pandas to import dataset.
I need to import dataset from url - https://newonlinecourses.science.psu.edu/stat501/sites/onlinecourses.science.psu.edu.stat501/files/data/leukemia_remission/index.txt
and convert it to csv file, I am getting some special character in converted csv -> ��
I am download txt file and converting it to csv, is is the right approach?
and converted csv is putting entire text into one column
from urllib.request import urlretrieve
import pandas as pd
from pandas import DataFrame
url = 'https://newonlinecourses.science.psu.edu/stat501/sites/onlinecourses.science.psu.edu.stat501/files/data/leukemia_remission/index.txt'
urlretrieve(url, 'index.txt')
df = pd.read_csv('index.txt', sep='/t', engine='python', lineterminator='\r\n')
csv_file = df.to_csv('index.csv', sep='\t', index=False, header=True)
print(csv_file)
after successful import, I have to Extract X as all columns except the first column and Y as first column also.
I'll appreciate your all help.
from urllib.request import urlretrieve
import pandas as pd
url = 'https://newonlinecourses.science.psu.edu/stat501/sites/onlinecourses.science.psu.edu.stat501/files/data/leukemia_remission/index.txt'
urlretrieve(url, 'index.txt')
df = pd.read_csv('index.txt', sep='\t',encoding='utf-16')
Y = df[['REMISS']]
X = df.drop(['REMISS'],axis=1)
Related
I am trying to run the below script to add to columns to the left of a file; however it keeps giving me
valueError: header must be integer or list of integers
Below is my code:
import pandas as pd
import numpy as np
read_file = pd.read_csv("/home/ex.csv",header='true')
df=pd.DataFrame(read_file)
def add_col(x):
df.insert(loc=0, column='Creation_DT', value=pd.to_datetime('today'))
df.insert(loc=1, column='Creation_By', value="Sean")
df.to_parquet("/home/sample.parquet")
add_col(df)
Any ways to make the creation_dt column a string?
According to pandas docs header is row number(s) to use as the column names, and the start of the data and must be int or list of int. So you have to pass header=0 to read_csv method.
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html
Also, pandas automatically creates dataframe from read file, you don't need to do it additionally. Use just
df = pd.read_csv("/home/ex.csv", header=0)
You can try:
import pandas as pd
import numpy as np
read_file = pd.read_csv("/home/ex.csv")
df=pd.DataFrame(read_file)
def add_col(x):
df.insert(loc=0, column='Creation_DT', value=str(pd.to_datetime('today')))
df.insert(loc=1, column='Creation_By', value="Sean")
df.to_parquet("/home/sample.parquet")
add_col(df)
I can not read the csv file in my jupiternotebook, the following is the link github link of the csv file
https://github.com/roshanthokchom/new-assignment/blob/master/spam.csv
import numpy as np
import pandas as pd
from sklearn.naive_bayes import GaussianNB
import urllib
pd.read_csv('spam.csv',encoding='latin-1')
ParserError: Error tokenizing data. C error: Expected 2 fields in line 13, saw 4
#Roshan here is the solution to your problem:
import pandas as pd
import csv
with open('spam.csv', newline='') as f:
csvread = csv.reader(f)
raw_data = list(csvread)
data = []
for i in batch_data:
i = i[0].split("\t")
data.append(i)
final_data = pd.DataFrame(data)
You can specify encoding as you have done but your file consists of commas in between text so if you read normally pandas will separate data based on ",". Thats why you are getting an error
I am trying to use below code to get posts with specific keywords from my csv file but I keep getting KeyErro "Tag1"
import re
import string
import pandas as pd
import openpyxl
import glob
import csv
import os
import xlsxwriter
import numpy as np
keywords = {"agile","backlog"}
# all your keywords
df = pd.read_csv(r"C:\Users\ferr1982\Desktop\split1_out.csv",
error_bad_lines=False)#, sep="," ,
encoding="utf-8")
output = pd.DataFrame(columns=df.columns)
for i in range(len(df.index)):
#if (df.loc[df['Tags'].isin(keywords)]):
if any(x in ((df['Tags1'][i]),(df['Tags2'][i]), (df['Tags3'][i] ),
(df['Tags4'][i]) , (df['Tags5'][i])) for x in keywords):
output.loc[len(output)] = [df[j][i] for j in df.columns]
output.to_csv("new_data5.csv", incdex=False)
Okay, it turned to be that there is a little space before "Tags" column in my CSV file !
it is working now after I added the space to the name in the code above.
I use pandas to load a csv file and want to print out data of row, here is original data
orginal data
I want to print out 'violence' data for make a bar chart, but it occuar a keyerror, here is my code
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
c_data=pd.read_csv('crime.csv')
print(c_data.head())
print (c_data['violence'])
and the error
error detail
error detail
I tried use capital VIOLENCE,print (c_data['VIOLENCE']),but also failed
error detail
error detail
can someone tell me how to work it out?
Try the following if your data is small:
with open('crime.csv', 'r') as my_file:
reader = csv.reader(my_file)
rows = list(reader)
print rows[3]
If your data is big, try this:
from itertools import islice
with open('crime.csv', 'r') as my_file:
reader = csv.reader(my_file)
print next(islice(reader, 3, 4))
I have an excel file with string stored in each cell:
rtypl srtyn OCVXZ srtyn
KPLNV KLNWZ bdfgh KLNWZ
xcvwh mvwhd WQKXM mvwhd
GYTR xvnm YTZN YTZN
ngws jklp PLNM jklp
I wanted to read excel file and write it in csv file. As you can see below:
import pandas as np
import csv
df = pd.read_excel(file, encoding='utf-16')
words= open("words.csv",'wb')
wr = csv.writer(words, dialect='excel')
for item in df:
wr.writerow(item)
But it reads the each line in separated alphabet and not as a string.
r,t,y,p,l
I am limited to write file as csv as I gonna use the result in a library that has lots of facility for csv file. Any advice on how I can read all the rows as a string in the cell is appreciated.
You can try the easiest solution:
# -*- coding: utf-8 -*-
import pandas as pd
df = pd.read_excel(file, encoding='utf-16')
df.to_csv('words.csv', encoding='utf-16')
Adding to zipa : If excel has multiple sheets : you can also try
import pandas as pd
df = pd.read_excel(file, 'Sheet1')
df.to_csv('words.csv')
Refer :
http://www.gregreda.com/2013/10/26/intro-to-pandas-data-structures/