PYTHON

# load multiple csv files into dataframe

# load multiple csv files into dataframe
import glob
import pandas as pd
csv_files = glob.glob("/content/sample_data/*.csv")
df = [pd.read_csv(filename) for filename in csv_files]

pandas dataframe from multiple csv

# credit to Stack Overflow user in source link

import pandas as pd
import glob

path = r'C:DRODCL_rawdata_files' # use your path
all_files = glob.glob(path + "/*.csv")

li = []

for filename in all_files:
    df = pd.read_csv(filename, index_col=None, header=0)
    li.append(df)

frame = pd.concat(li, axis=0, ignore_index=True)

read multiple csv files into separate dataframes python

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])