Python - 从 csv 读取数据，然后使用循环中的数据和文件号写入新的 csv

Question

My objective is to:

• Read in all of the files from the directory which start with letter "Z".
• Read in the Temperature column from each.csv in the directory.
• Open a new. csv :
  • Add the Temperature column to the new. csv .
  • Add a column, "File #" to this new .csv , and iterate 1,2,3,4 based on the number of files that I read in through the loop.
• I'm currently stuck with how to:
  • Create the.csv file and open it in every loop.
  • Add the Temperature Column and the File # column (with File # incremented) into the.csv file.

import pandas as pd import csv from glob import glob
filenames = glob("C:/Users/Z*.csv")

for f in filenames:
    df = pd.read_csv(f, sep=',',skiprows=24)
    df.columns=['sample','Time','ms','Temperature']
    df=df.astype(str)
    df["Temperature"] = df["Temperature"].str.replace('\+ ', '').str.replace(' ', '').astype(float)
    
    # I need to add the column, "File #" to the Dataframe

    df.to_csv('my_csv.csv', mode='a', columns=[['Temperature','File #']] header=False)
    # Is df.to_csv is the best option here?
    
    # Then, I need to iterate the file # for the next loop.

Answer 1

please find my suggestions below - hope this helps!

for i, f in enumerate(filenames):
    df = pd.read_csv(f, sep=',',skiprows=24)
    df.columns=['sample','Time','ms','Temperature']
    df=df.astype(str)
    df["Temperature"] = df["Temperature"].str.replace('\+ ', '').str.replace(' ', '').astype(float)
    
    # I need to add the column, "File #" to the Dataframe
    df['File #'] = i
    
    df.to_csv('my_csv.csv', mode='a', columns=[['Temperature','File #']] header=False)
    # Is df.to_csv is the best option here? - probably yes