Read Multiple CSV Files into Separate Data Frames

Read multiple CSV files into separate data frames

Quick draft, untested:

1. Use list.files() aka dir() to dynamically generate your list of files.

2. This returns a vector, just run along the vector in a for loop.

3. Read the i-th file, then use assign() to place the content into a new variable file_i

That should do the trick for you.

Read in multiple csv into separate dataframes in Pandas

You can list all csv under a directory using os.listdir(dirname) and combine it with os.path.basename to parse the file name.

import os

# current directory csv files
csvs = [x for x in os.listdir('.') if x.endswith('.csv')]
# stats.csv -> stats
fns = [os.path.splitext(os.path.basename(x))[0] for x in csvs]

d = {}
for i in range(len(fns)):
    d[fns[i]] = pd.read_csv(csvs[i])

reading multiple csv and saving into separate dataframes

seems like you're overwriting the same variable again and again

path = os.getcwd()
csv_files = glob.glob(os.path.join(r'blabla/Data', "*.csv" ))

list_of_dfs = []

for f in csv_files:
    df = pd.read_csv(f)
    print('Location:', f)
    print('File Name:', f.split("\\")[-1])
    print('Content:')
    df.pop('Unnamed: 0')
    display(df)
    list_of_dfs.append(df)

access the individual dataframes with list_of_dfs[0], list_of_dfs[1],...

How to load multiple csv files into seperate objects(dataframes) in R based on filename?

Solution for anyone curious...

files <- list.files(pattern = ".*csv")

for(file in 1:length(files)) { 
  file_name <- paste(c("file00",file), collapse = " ")
  file_name <- gsub(" ", "", file_name, fixed = TRUE)
  ex_file_name <- paste(c("exfile00",file), collapse = " ")
  ex_file_name <- gsub(" ", "", ex_file_name, fixed = TRUE)
  
  file_object <- read.csv(file = paste(file_name, ".csv", sep=""),fileEncoding="UTF-8-BOM")
  exfile_object <- read.csv(file = paste(ex_file_name, ".csv", sep=""),fileEncoding="UTF-8-BOM")
  }

Essentially build the filename within the loop, then passs it to the readcsv function on each iteration.

Reading multiple files into separate data frames

You can probably do something like this:

import glob
d = {}
base_name = "df{}"
flag = 0

for filename in glob.glob('*.xlsx'):
    d[base_name.format(flag)] = pd.read_excel(filename, sheet_name = 'Bilan')
    flag += 1

Here you create a base_name for your name and a flag to track the position of your file and then use those variables to construct a full filename.

Read multiple CSV files and replacing names

If you want to name each data frame you can read it into a list with lapply and rename the elements of the list. Now you can access the data frames in the list. Also, you can use the three-letter abbreviations for the English month names, month.abb.:

filenames = list.files(path = "C:/R/month_data/",
                       pattern = "2021-+.*csv")
filepath = paste0("C:/R/month_data/", filenames)

dfs <- lapply(filepath, read.csv)
names(dfs) <- month.abb

View(dfs$Jan)

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