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Python import csv file and replace blank values

I have just started a data quality class in which I got zero instruction on Python but am expected to create a script. There are three instructions for my Python script:
Create a script that loads an entire CSV file and replace all the blank values to NAN
Use genfromtxt function
Write the results set into a different file
I have been working on this for a few hours, but with no previous experience with Python, I am completely stuck! This is what I have so far:
import csv
file = open(quality.csv, 'r')
csvreader = csv.reader(file)
header = next(csvreader)
print(header)
rows = []
for row in csvreader:
rows.append(row)
print(rows)
My first problem is that when I tried using genfromtxt, it would not print out the headers or the entire csv file, it would only print out a few lines. If it matters, all of the values of the csv file are ints/floats, but the headers are strings.
See here
The next problem is I have tried several different ways to replace blank values, but I was not successful. All of the blank fields in this file are in the last column. When I print out the csv in full, this is what the line looks like (I've highlighted the empty value):
See here
Finally, I have no idea what instruction #3 means. I am completely new at this with zero Python knowledge! I think I am unsure of the Python syntax and rules - which I will look into more and learn, however I only had two days to complete this assignment and I do not know anything yet! Thank you in advance.

What you did with genfromtxt seems correct already. With big data like this, terminal only shows some data from the beginning and at the end, and those 3 dots in the middle also indicates the other records you're not seeing there!

Search Delete using csv.reader in python

I want to search a column and delete from csv file using python. I cannot dataframes as I need to work with large files and can't load it in RAM. How to do it?
example csv file-
Home,Contact,Adress
abc,123,xyz
I need to find and delete Contact for example. I thought to use csv.reader but cannot figure out how to do it

Check this :
import csv
col = 'Contact'
with open('your_csv.csv') as f:
with open('new_csv.csv', 'w', newline='') as g:
# creating csv reader
reader = csv.reader(f)
# getting the 'col' index in the header, we want to delete it in the next lines
col_index = next(reader).index(col)
for line in reader:
del line[col_index]
# writing to new csv file
writer = csv.writer(g)
writer.writerow(line)
Explanation for using newline='' is here.

If your application prefers to work with pandas still, I'd suggest to play with pandas chunking tactic. See example below:
iterator = pandas.read_csv('/tmp/abc.csv', chunksize=10**5)
df_new = pandas.DataFrame(columns=['your_remaining_columns'])
for df in iterator:
del df['col_b']
df_new = pandas.concat([df_new, df])
print(df_new.shape[0])
print(df_new.columns)
I was able to process a 50GB csv file with complex data (non utf8 encoding, cell contains ,, doing deduplication and filtered out bad rows) by this approach before.

Storing DataFrame output utilizing Pandas to either csv or MySql DB

question regarding pandas:
Say I created a dataframe and generated output under separate variables, rather than printing them, how would I go about combining them back into another dataframe correctly to either send as a CSV and then upload to a DB or directly upload to a DB?
Everything works fine code wise, I just haven't really seen or know of the best practice to do this. I know we can store things in list, dict, etc
What I did was:
#imported all modules
object = df.iloc[0,0]
#For loop magic goes here
#nested for loop
#if conditions are met, do this
result = df.iloc[i, k+1]
print(object, result)
I've also stored them into a separate DataFrame trying:
df2 = pd.DataFrame({'object': object, 'result' : result}, index=[0])
df2.to_csv('output.csv', index=False, mode='a')
The only problem with that is that it appends everything to each row, most likely do to the append and perhaps not including it in the for loop. Which is odd because the raw output is EXACTLY how I'm trying to get it into a csv or into a DB
As saying though, looking to combine both values back into a dataframe for speed. I tried concat etc, but no luck, so I was wondering what the correct format would be? Thanks

So it turns out that after more research and revising, I solved my issue
Referenced this and personal revisions, this is a basis of what I did:
Empty space in between rows after using writer in python
import csv
/* Had to wrap in a for loop that is not listed and append to file while clearing it first to remove spaces in each row*/
with open('csvexample.csv', wb+, newline='') as file:
reader = csv.reader(file)
for row in reader:
print(row)
Additional supporting material:
Confused by python file mode "w+"

python csv reader not reading all rows

So I've got about 5008 rows in a CSV file, a total of 5009 with the headers. I'm creating and writing this file all within the same script. But when i read it at the end, with either pandas pd.read_csv, or python3's csv module, and print the len, it outputs 4967. I checked the file for any weird characters that may be confusing python but don't see any. All the data is delimited by commas.
I also opened it in sublime and it shows 5009 rows not 4967.
I could try other methods from pandas like merge or concat, but if python wont read the csv correct, that's no use.
This is one method i tried.
df1=pd.read_csv('out.csv',quoting=csv.QUOTE_NONE, error_bad_lines=False)
df2=pd.read_excel(xlsfile)
print (len(df1))#4967
print (len(df2))#5008
df2['Location']=df1['Location']
df2['Sublocation']=df1['Sublocation']
df2['Zone']=df1['Zone']
df2['Subnet Type']=df1['Subnet Type']
df2['Description']=df1['Description']
newfile = input("Enter a name for the combined csv file: ")
print('Saving to new csv file...')
df2.to_csv(newfile, index=False)
print('Done.')
target.close()
Another way I tried is
dfcsv = pd.read_csv('out.csv')
wb = xlrd.open_workbook(xlsfile)
ws = wb.sheet_by_index(0)
xlsdata = []
for rx in range(ws.nrows):
xlsdata.append(ws.row_values(rx))
print (len(dfcsv))#4967
print (len(xlsdata))#5009
df1 = pd.DataFrame(data=dfcsv)
df2 = pd.DataFrame(data=xlsdata)
df3 = pd.concat([df2,df1], axis=1)
newfile = input("Enter a name for the combined csv file: ")
print('Saving to new csv file...')
df3.to_csv(newfile, index=False)
print('Done.')
target.close()
But not matter what way I try the CSV file is the actual issue, python is writing it correctly but not reading it correctly.
Edit: Weirdest part is that i'm getting absolutely no encoding errors or any errors when running the code...
Edit2: Tried testing it with nrows param in first code example, works up to 4000 rows. Soon as i specify 5000 rows, it reads only 4967.
Edit3: manually saved csv file with my data instead of using the one written by the program, and it read 5008 rows. Why is python not writing the csv file correctly?

I ran into this issue also. I realized that some of my lines had open-ended quotes, which was for some reason interfering with the reader.
So for example, some rows were written as:
GO:0000026 molecular_function "alpha-1
GO:0000027 biological_process ribosomal large subunit assembly
GO:0000033 molecular_function "alpha-1
and this led to rows being read incorrectly. (Unfortunately I don't know enough about how csvreader works to tell you why. Hopefully someone can clarify the quote behavior!)
I just removed the quotes and it worked out.
Edited: This option works too, if you want to maintain the quotes:
quotechar=None

My best guess without seeing the file is that you have some lines with too many or not enough commas, maybe due to values like foo,bar.
Please try setting error_bad_lines=True. From Pandas documentation: http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html to see if it catches lines with errors in them, and my guess is that there will be 41 such lines.
error_bad_lines : boolean, default True
Lines with too many fields (e.g. a csv line with too many commas) will by default cause an exception to be raised, and no DataFrame will be returned. If False, then these “bad lines” will dropped from the DataFrame that is returned. (Only valid with C parser)
The csv.QUOTE_NONE option seems to not quote fields and replace the current delimiter with escape_char + delimiter when writing, but you didn't paste your writing code, but on read it's unclear what this option does. https://docs.python.org/3/library/csv.html#csv.Dialect

From Excel to Python: from columns to strings

I have an Excel file with 2 columns (it is an CSV file). The first contains dates, while the second contains numbers.
I want to make a list out of this with Python, the following way: ['date1','number1','date2','number2']. At the moment I always get: ['date1;number1','date2;number2']. I basically want every element to be treated as a string on its own.
At the moment I'm using following code:
abc = []
with open('C:...doc.csv', 'r', encoding = "utf8") as f:
reader = csv.reader(f)
for row in reader:
abc.extend([row])
I've tried everything I could come up with, e.g. nested for etc, but nothing seems to work.
Can anyone help me out please? Thank you!