I am sometimes using Python for some automation stuff. I just came around a Problem I am not able to solve.
I use Python 3.3.
I have a .csv file opened as a DictReader. Now I want, depending on a condition, to delete a row in the DictReader.
The code looks pretty much like:
reader = csv.DictReader(csvfile, delimiter = ";")
...
if True:
del reader[row]
Well, Python tells me that: "the dictReader object does not support item deletion".
Something there I am totally missing? Is there a built-in way to do it and I just did not find it in the manual, or do I have to use some kind of workaround?
best regards,
moritz
Related
im a noobie in python. I want to get some data from csv with pandas and after write a new csv file with extra data in format
"type";"currency";"amount";"comment"
"type1";"currency1";"amount1";"comment1"
etc
import pandas as pd
import csv
req=pd.read_csv('/Users/user/web/python/Bookcopy.csv')
type="type"
comment = "2week"
i=0
while i<3:
Currency = req['Currency'].values[i]
ReqAmount = req['Request'].values[i]
r = round(ReqAmount,-1)
i+=1
data =[type,Currency,r,comment]
#print(data)
csv_file = open('data2.csv', 'w')
with csv_file:
writer = csv.writer(csv_file)
writer.writerow(data)
print("DONE")
writer.writerows(data)
_csv.Error: iterable expected, not numpy.float64
I have multiple things to criticize here. I hope it doesn't come across mean, but rather educational. While your code would work regardless of those points, it is good coding style to follow them.
Variables should not start with a capital letter. Currency and ReqAmount should be currency and reqAmount.
Don't use keywords for variable names. type is a python keyword.
Make sure your formatting doesn't get destroyed when posting here. Especially for python, which relies on tab formatting. Read here for more information: https://stackoverflow.com/editing-help#code
That said, let me try to go through your code and give you tips and tricks:
Don't run code in python directly. Always use the main() method. It's just better coding style.
When looping, don't use the i=0; while i<3; i+=1 construct, rather use for i in range(3). While it works, it is not very pythonic and a lot harder to read.
Never assume anything that cannot be guaranteed in your code. In this case, you assume that the csv-file has at least 3 lines, otherwise your program would crash. Instead, read the number of lines from the csv file, with len(req).
data =[type,Currency,r,comment] keeps overwriting your data variable. You could either append to data and then write everything to the output file at the end, or directly write to the output file in every iteration.
Don't use open to create a variable (except absolutely necessary). Instead, use open in a with statement. This ensures that the file will get closed properly. I have seen that you do use the with statement, nonetheless you usually use it like with open(...) as variable_name:.
CSV files usually start with the column names. Therefore you should write the column names before you write data.
I won't fix that, because it will change the appearance of the program completely, but normally, don't mix different libraries. If you use pandas for csv reading, also use it for writing. If you use the csv library for writing, also use it for reading. While it isn't wrong to mix them, it is bad style and creates more dependencies than would be necessary.
I don't really understand what your code is supposed to do, so I just guess and hope it goes in the right direction.
When fixing all those points, you might have something like that:
import pandas as pd
import csv
def main():
req=pd.read_csv('/Users/user/web/python/Bookcopy.csv')
transferType = "type"
comment = "2week"
with open('data2.csv', 'w') as csv_file:
writer = csv.writer(csv_file)
writer.writerow(["type","currency","amount","comment"])
for i in range(len(req)):
currency = req['Currency'].values[i]
reqAmount = req['Request'].values[i]
r = round(reqAmount,-1)
data = [transferType,currency,r,comment]
#print(data)
writer.writerow(data)
print("DONE")
# Whenever you run a program, __name__ will be set to '__main__' in the initial
# script. This makes it easier later when you work with multiple code files.
if __name__ == '__main__':
main()
I have a file some crazy stuff in it. It looks like this:
I attempted to get rid of it using this:
df['firstname'] = map(lambda x: x.decode('utf-8','ignore'), df['firstname'])
But I wound up with this in my dataframe: <map object at 0x0000022141F637F0>
I got that example from another question and this seems to be the Python3 method for doing this but I'm not sure what I'm doing wrong.
Edit: For some odd reason someone thinks that this has something to do with getting a map to return a list. The central issue is getting rid of non UTF-8 characters. Whether or not I'm even doing that correctly has yet to be established.
As I understand it, I have to apply an operation to every character in a column of the dataframe. Is there another technique or is map the correct way and if it is, why am I getting the output I've indicated?
Edit2: For some reason, my machine wouldn't let me create an example. I can now. This is what i'm dealing with. All those weird characters need to go.
import pandas as pd
data = [['🦎Ale','Αλέξανδρα'],['��Grain','Girl🌾'],['Đỗ Vũ','ên Anh'],['Don','Johnson']]
df = pd.DataFrame(data,columns=['firstname','lastname'])
print(df)
Edit 3: I tired doing this using a reg ex and for some reason, it still didn't work.
df['firstname'] = df['firstname'].replace('[^a-zA-z\s]',' ')
This regex works FINE in another process, but here, it still leaves the ugly characters.
Edit 4: It turns out that it's image data that we're looking at.
script that reads CSV files and gets headers and filter by specific column, I have tried researching on it but nothing of quality I have managed to get.
Please any help will be deeply appreciated
There's a standard csv library included with Python.
https://docs.python.org/3/library/csv.html
It will automatically create a dictionary of arrays where the first row in the CSV determines the keys in the dict.
You can also follow pandas.read_csv for the same.
I'm coming from R + Rstudio. In RStudio, you can save objects to an .RData file using save()
save(object_to_save, file = "C:/path/where/RData/file/will/be/saved.RData")
You can then load() the objects :
load(file = "C:/path/where/RData/file/was/saved.RData")
I'm now using Spyder and Python3, and I was wondering if the same thing is possible.
I'm aware everything in the globalenv can be saved to a .spydata using this :
But I'm looking for a way to save to a .spydata file in the code. Basically, just the code under the buttons.
Bonus points if the answer includes a way to save an object (or multiple objects) and not the whole env.
(Please note I'm not looking for an answer using pickle or shelve, but really something similar to R's load() and save().)
(Spyder developer here) There's no way to do what you ask for with a command in Spyder consoles.
If you'd like to see this in a future Spyder release, please open an issue in our issues tracker about it, so we don't forget to consider it.
Considering the comment here, we can
rename the file from .spydata to .tar
extract the file (using file manager, for example). It will deliver a file .pickle (and maybe a .npy)
extract the objects saved from the environment:
import pickle
with open(path, 'rb') as f:
data_temp = pickle.load(f)
that object will be a dictionary with the objects saved.
import xlwt
wb = xlwt.Workbook()
sheet1 = wb.add_sheet('Sheet 1')
wb.save('self, example.xls')
I am trying to learn how to create xls, edit xls, or delete if neccesary on python. I had verymuch trouble on this because every tutorial online doesn't mentions that I should put xlwt before Workbook but I figure it out now. The problem is when I run this code I get an error wich it says "ValueError: cannot use LOCALE flag with a str pattern" I don't even know what that means... What is it about and how can I fix it?
There is a known-issue with tablib and Python 3.6, looks like it will be solved in the next releases.
For now, I make it work just downgrading to python 3.5.2
I had a similar problem and i resolved it by changing my series to "str" data type. df.astype("str")
Also not sure why you are trying to save your file as "self, example.xls". Could you print the entire error as it was given.