I am new to Python. I have used just letters to simplify my code below.My code writes a CSV file with columns of a,b,c,d values,each has 10 rows (length). I would like to add the average value of c and d to the same CSV file as well as an additional two columns each have one row for ave values. I have tried to append field names and write the new values but it didn't work.
with open('out.csv', 'w') as csvfile:
fieldnames=['a','b','c','d']
csv_writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
csv_writer.writeheader()
total_c=0
total_d=0
for i in range(1,length):
do something get a,b,c,d values.
total_c += c
total_d += d
csv_writer.writerow({'a': a,'b':b,'c':c,'d':d })
mean_c=total_c /length
mean_c=total_c /length
I expect to see something in the picture:
Try to use pandas library to deal with csv file. I provided sample code below, I assume that csv file has no header present on the first line.
import pandas as pd
data = pd.read_csv('out.csv',header=[['a','b','c','d'])
#making sure i am using copy of dataframe
avg_data = data.copy()
#creating new columns average in same dataframe
avg_data['mean_c'] = avg_data.iloc[:,2].mean(axis=1)
avg_data['mean_d'] = avg_data.iloc[:,3].mean(axis=1)
# writing updated data to csv file
avg_data.to_csv('out.csv', sep=',', encoding='utf-8')
I am new to python. I have a .csv file which has 13 columns. I want to round off the floating values of the 2nd column which I was able to achieve successfully. I did this and stored it in a list. Now I am unable to figure out how to overwrite the rounded off values into the same csv file and into the same column i.e. column 2? I am using python3. Any help will be much appreciated.
My code is as follows:
Import statements for module import:
import csv
Creating an empty list:
list_string = []
Reading a csv file
with open('/home/user/Desktop/wine.csv', 'r') as csvDataFile:
csvReader = csv.reader(csvDataFile, delimiter = ',')
next(csvReader, None)
for row in csvReader:
floatParse = float(row[1])
closestInteger = int(round(floatParse))
stringConvert = str(closestInteger)
list_string.append(stringConvert)
print(list_string)
Writing into the same csv file for the second column (Overwrites the entire Excel file)
with open('/home/user/Desktop/wine.csv', 'w') as csvDataFile:
writer = csv.writer(csvDataFile)
next(csvDataFile)
row[1] = list_string
writer.writerows(row[1])
PS: The writing into the csv overwrites the entire csv and removes all the other columns which I don't want. I just want to overwrite the 2nd column with rounded off values and keep the rest of the data same.
this might be what you're looking for.
import pandas as pd
import numpy as np
#Some sample data
data = {"Document_ID": [102994,51861,51879,38242,60880,76139,76139],
"SecondColumnName": [7.256,1.222,3.16547,4.145658,4.154656,6.12,17.1568],
}
wine = pd.DataFrame(data)
#This is how you'd read in your data
#wine = pd.read_csv('/home/user/Desktop/wine.csv')
#Replace the SecondColumnName with the real name
wine["SecondColumnName"] = wine["SecondColumnName"].map('{:,.2f}'.format)
#This will overwrite the sheet, but it will have all the data as before
wine.to_csv(/home/user/Desktop/wine.csv')
Pandas is way easier than read csv...I'd recommended checking it out.
I think this better answers the specific question. The key to this is to define an input_file and an output_file during the with part.
The StringIO part is just there for sample data in this example. newline='' is for Python 3. Without it, blank lines between each row appears in the output. More info.
import csv
from io import StringIO
s = '''A,B,C,D,E,F,G,H,I,J,K,L
1,4.4343,3,4,5,6,7,8,9,10,11
1,8.6775433,3,4,5,6,7,8,9,10,11
1,16.83389832,3,4,5,6,7,8,9,10,11
1,32.2711122,3,4,5,6,7,8,9,10,11
1,128.949483,3,4,5,6,7,8,9,10,11'''
list_string = []
with StringIO(s) as input_file, open('output_file.csv', 'w', newline='') as output_file:
reader = csv.reader(input_file)
next(reader, None)
writer = csv.writer(output_file)
for row in reader:
floatParse = float(row[1]) + 1
closestInteger = int(round(floatParse))
stringConvert = str(closestInteger)
row[1] = stringConvert
writer.writerow(row)
I have a csv file with the following columns:
id,name,age,sex
Followed by a lot of values for the above columns.
I am trying to read the column names alone and put them inside a list.
I am using Dictreader and this gives out the correct details:
with open('details.csv') as csvfile:
i=["name","age","sex"]
re=csv.DictReader(csvfile)
for row in re:
for x in i:
print row[x]
But what I want to do is, I need the list of columns, ("i" in the above case)to be automatically parsed with the input csv than hardcoding them inside a list.
with open('details.csv') as csvfile:
rows=iter(csv.reader(csvfile)).next()
header=rows[1:]
re=csv.DictReader(csvfile)
for row in re:
print row
for x in header:
print row[x]
This gives out an error
Keyerrror:'name'
in the line print row[x]. Where am I going wrong? Is it possible to fetch the column names using Dictreader?
Though you already have an accepted answer, I figured I'd add this for anyone else interested in a different solution-
Python's DictReader object in the CSV module (as of Python 2.6 and above) has a public attribute called fieldnames.
https://docs.python.org/3.4/library/csv.html#csv.csvreader.fieldnames
An implementation could be as follows:
import csv
with open('C:/mypath/to/csvfile.csv', 'r') as f:
d_reader = csv.DictReader(f)
#get fieldnames from DictReader object and store in list
headers = d_reader.fieldnames
for line in d_reader:
#print value in MyCol1 for each row
print(line['MyCol1'])
In the above, d_reader.fieldnames returns a list of your headers (assuming the headers are in the top row).
Which allows...
>>> print(headers)
['MyCol1', 'MyCol2', 'MyCol3']
If your headers are in, say the 2nd row (with the very top row being row 1), you could do as follows:
import csv
with open('C:/mypath/to/csvfile.csv', 'r') as f:
#you can eat the first line before creating DictReader.
#if no "fieldnames" param is passed into
#DictReader object upon creation, DictReader
#will read the upper-most line as the headers
f.readline()
d_reader = csv.DictReader(f)
headers = d_reader.fieldnames
for line in d_reader:
#print value in MyCol1 for each row
print(line['MyCol1'])
You can read the header by using the next() function which return the next row of the reader’s iterable object as a list. then you can add the content of the file to a list.
import csv
with open("C:/path/to/.filecsv", "rb") as f:
reader = csv.reader(f)
i = reader.next()
rest = list(reader)
Now i has the column's names as a list.
print i
>>>['id', 'name', 'age', 'sex']
Also note that reader.next() does not work in python 3. Instead use the the inbuilt next() to get the first line of the csv immediately after reading like so:
import csv
with open("C:/path/to/.filecsv", "rb") as f:
reader = csv.reader(f)
i = next(reader)
print(i)
>>>['id', 'name', 'age', 'sex']
The csv.DictReader object exposes an attribute called fieldnames, and that is what you'd use. Here's example code, followed by input and corresponding output:
import csv
file = "/path/to/file.csv"
with open(file, mode='r', encoding='utf-8') as f:
reader = csv.DictReader(f, delimiter=',')
for row in reader:
print([col + '=' + row[col] for col in reader.fieldnames])
Input file contents:
col0,col1,col2,col3,col4,col5,col6,col7,col8,col9
00,01,02,03,04,05,06,07,08,09
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
50,51,52,53,54,55,56,57,58,59
60,61,62,63,64,65,66,67,68,69
70,71,72,73,74,75,76,77,78,79
80,81,82,83,84,85,86,87,88,89
90,91,92,93,94,95,96,97,98,99
Output of print statements:
['col0=00', 'col1=01', 'col2=02', 'col3=03', 'col4=04', 'col5=05', 'col6=06', 'col7=07', 'col8=08', 'col9=09']
['col0=10', 'col1=11', 'col2=12', 'col3=13', 'col4=14', 'col5=15', 'col6=16', 'col7=17', 'col8=18', 'col9=19']
['col0=20', 'col1=21', 'col2=22', 'col3=23', 'col4=24', 'col5=25', 'col6=26', 'col7=27', 'col8=28', 'col9=29']
['col0=30', 'col1=31', 'col2=32', 'col3=33', 'col4=34', 'col5=35', 'col6=36', 'col7=37', 'col8=38', 'col9=39']
['col0=40', 'col1=41', 'col2=42', 'col3=43', 'col4=44', 'col5=45', 'col6=46', 'col7=47', 'col8=48', 'col9=49']
['col0=50', 'col1=51', 'col2=52', 'col3=53', 'col4=54', 'col5=55', 'col6=56', 'col7=57', 'col8=58', 'col9=59']
['col0=60', 'col1=61', 'col2=62', 'col3=63', 'col4=64', 'col5=65', 'col6=66', 'col7=67', 'col8=68', 'col9=69']
['col0=70', 'col1=71', 'col2=72', 'col3=73', 'col4=74', 'col5=75', 'col6=76', 'col7=77', 'col8=78', 'col9=79']
['col0=80', 'col1=81', 'col2=82', 'col3=83', 'col4=84', 'col5=85', 'col6=86', 'col7=87', 'col8=88', 'col9=89']
['col0=90', 'col1=91', 'col2=92', 'col3=93', 'col4=94', 'col5=95', 'col6=96', 'col7=97', 'col8=98', 'col9=99']
How about
with open(csv_input_path + file, 'r') as ft:
header = ft.readline() # read only first line; returns string
header_list = header.split(',') # returns list
I am assuming your input file is CSV format.
If using pandas, it takes more time if the file is big size because it loads the entire data as the dataset.
I am just mentioning how to get all the column names from a csv file.
I am using pandas library.
First we read the file.
import pandas as pd
file = pd.read_csv('details.csv')
Then, in order to just get all the column names as a list from input file use:-
columns = list(file.head(0))
Thanking Daniel Jimenez for his perfect solution to fetch column names alone from my csv, I extend his solution to use DictReader so we can iterate over the rows using column names as indexes. Thanks Jimenez.
with open('myfile.csv') as csvfile:
rest = []
with open("myfile.csv", "rb") as f:
reader = csv.reader(f)
i = reader.next()
i=i[1:]
re=csv.DictReader(csvfile)
for row in re:
for x in i:
print row[x]
here is the code to print only the headers or columns of the csv file.
import csv
HEADERS = next(csv.reader(open('filepath.csv')))
print (HEADERS)
Another method with pandas
import pandas as pd
HEADERS = list(pd.read_csv('filepath.csv').head(0))
print (HEADERS)
import pandas as pd
data = pd.read_csv("data.csv")
cols = data.columns
I literally just wanted the first row of my data which are the headers I need and didn't want to iterate over all my data to get them, so I just did this:
with open(data, 'r', newline='') as csvfile:
t = 0
for i in csv.reader(csvfile, delimiter=',', quotechar='|'):
if t > 0:
break
else:
dbh = i
t += 1
Using pandas is also an option.
But instead of loading the full file in memory, you can retrieve only the first chunk of it to get the field names by using iterator.
import pandas as pd
file = pd.read_csv('details.csv'), iterator=True)
column_names_full=file.get_chunk(1)
column_names=[column for column in column_names_full]
print column_names
I have two files, the first one is called book1.csv, and looks like this:
header1,header2,header3,header4,header5
1,2,3,4,5
1,2,3,4,5
1,2,3,4,5
The second file is called book2.csv, and looks like this:
header1,header2,header3,header4,header5
1,2,3,4
1,2,3,4
1,2,3,4
My goal is to copy the column that contains the 5's in book1.csv to the corresponding column in book2.csv.
The problem with my code seems to be that it is not appending right nor is it selecting just the index that I want to copy.It also gives an error that I have selected an incorrect index position. The output is as follows:
header1,header2,header3,header4,header5
1,2,3,4
1,2,3,4
1,2,3,41,2,3,4,5
Here is my code:
import csv
with open('C:/Users/SAM/Desktop/book2.csv','a') as csvout:
write=csv.writer(csvout, delimiter=',')
with open('C:/Users/SAM/Desktop/book1.csv','rb') as csvfile1:
read=csv.reader(csvfile1, delimiter=',')
header=next(read)
for row in read:
row[5]=write.writerow(row)
What should I do to get this to append properly?
Thanks for any help!
What about something like this. I read in both books, append the last element of book1 to the book2 row for every row in book2, which I store in a list. Then I write the contents of that list to a new .csv file.
with open('book1.csv', 'r') as book1:
with open('book2.csv', 'r') as book2:
reader1 = csv.reader(book1, delimiter=',')
reader2 = csv.reader(book2, delimiter=',')
both = []
fields = reader1.next() # read header row
reader2.next() # read and ignore header row
for row1, row2 in zip(reader1, reader2):
row2.append(row1[-1])
both.append(row2)
with open('output.csv', 'w') as output:
writer = csv.writer(output, delimiter=',')
writer.writerow(fields) # write a header row
writer.writerows(both)
Although some of the code above will work it is not really scalable and a vectorised approach is needed. Getting to work with numpy or pandas will make some of these tasks easier so it is great to learn a bit of it.
You can download pandas from the Pandas Website
# Load Pandas
from pandas import DataFrame
# Load each file into a pandas dataframe, this is based on a numpy array
data1 = DataFrame.from_csv('csv1.csv',sep=',',parse_dates=False)
data2 = DataFrame.from_csv('csv2.csv',sep=',',parse_dates=False)
#Now add 'header5' from data1 to data2
data2['header5'] = data1['header5']
#Save it back to csv
data2.to_csv('output.csv')
Regarding the "error that I have selected an incorrect index position," I suspect this is because you're using row[5] in your code. Indexing in Python starts from 0, so if you have A = [1, 2, 3, 4, 5] then to get the 5 you would do print(A[4]).
Assuming the two files have the same number of rows and the rows are in the same order, I think you want to do something like this:
import csv
# Open the two input files, which I've renamed to be more descriptive,
# and also an output file that we'll be creating
with open("four_col.csv", mode='r') as four_col, \
open("five_col.csv", mode='r') as five_col, \
open("five_output.csv", mode='w', newline='') as outfile:
four_reader = csv.reader(four_col)
five_reader = csv.reader(five_col)
five_writer = csv.writer(outfile)
_ = next(four_reader) # Ignore headers for the 4-column file
headers = next(five_reader)
five_writer.writerow(headers)
for four_row, five_row in zip(four_reader, five_reader):
last_col = five_row[-1] # # Or use five_row[4]
four_row.append(last_col)
five_writer.writerow(four_row)
Why not reading the files line by line and use the -1 index to find the last item?
endings=[]
with open('book1.csv') as book1:
for line in book1:
# if not header line:
endings.append(line.split(',')[-1])
linecounter=0
with open('book2.csv') as book2:
for line in book2:
# if not header line:
print line+','+str(endings[linecounter]) # or write to file
linecounter+=1
You should also catch errors if row numbers don't match.