WebNov 7, 2024 · I have a huge .csv file (over 1 million rows) and need to delete all data that is before 1st January 2010 at 00:00. Have tried googling how to do this but can't seem to find anything that doesn't use row numbers, rather than deleting by the date/time. I tried: df [ (df ['Date Time'].dt.year < 2010-0o1)] WebJan 30, 2014 · import csv reader = csv.reader (open ("info.csv", "rb"), delimiter=',') f = csv.writer (open ("final.csv", "wb")) for line in reader: if "Name" not in line: f.writerow (line) print line But the "Name" row isn't removed. What am I doing wrong? EDIT: I was using the wrong delimiter. Changing it to \t worked.
Delete rows and columns from a DataFrame using Pandas drop()
WebJul 21, 2024 · Read the .csv file into a dataframe: df = pd.read_csv ('output.csv') Then remove the first 16 rows: df.drop (df.head (16).index, inplace=True) and the last 16 rows: df.drop (df.tail (16).index, inplace=True) then save the .csv back to file: df.to_csv ('output_out.csv') Share Improve this answer Follow answered Jul 21, 2024 at 12:42 … WebJan 20, 2024 · I want to read a CSV file and delete a row in that CSV file based on three conditions, type, srcaddr, dstaddr. So for example, if i enter something like first condition is 'icmp', second condition is '10.0.0.1', third condition is '10.0.0.2', it … ell teaching jobs near me
Delete rows/columns from DataFrame using Pandas.drop() - GeeksforG…
WebSep 17, 2024 · Python Delete rows/columns from DataFrame using Pandas.drop () Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. … WebJul 15, 2024 · Simple, you iterate over the keys of the dict like this: values = [1002,1007,1008] for key in df.keys (): then you check if there are any of the values you want to remove in the value of that key values = [1002,1007,1008] for key in df.keys (): for value in values: if value in df [key]: df [key].remove (value) Step III WebJun 18, 2024 · 4 Answers Sorted by: 2 FILENAME = 'test.csv' DELETE_LINE_NUMBER = 1 with open (FILENAME) as f: data = f.read ().splitlines () # Read csv file with open (FILENAME, 'w') as g: g.write ('\n'.join ( [data [:DELETE_LINE_NUMBER]] + data [DELETE_LINE_NUMBER+1:])) # Write to file Original test.csv: ID, Name 0, ABC 1, … ell teachers