将目录中的所有文件连接到单个 CSV 时，Pandas 中的“EmptyDataError：没有要从文件中解析的列”

Question

So I'm working on a project that analyzes Covid-19 data from this entire year. I have multiple csv files in a given directory. I am trying to merge all the files' contents from each month into a single, comprehensive csv file. Here's what I got so far as shown below...Specifically, the error message that appears is 'EmptyDataError: No columns to parse from file.' If I were to delete df = pd.read_csv('./csse_covid_19_daily_reports_us/' + file) and simply run print(file) It lists all the correct files that I am trying to merge. However, when trying to merge all data into one I get that error message. What gives?

import pandas as pd
import os


df = pd.read_csv('./csse_covid_19_daily_reports_us/09-04-2020.csv')

files = [file for file in os.listdir('./csse_covid_19_daily_reports_us')]

all_data = pd.DataFrame()

for file in files:
    df = pd.read_csv('./csse_covid_19_daily_reports_us/' + file)
    all_data = pd.concat([all_data, df])

all_data.head()

Answer 1

Folks, I have resolved this issue. Instead of sifting through files with files = [file for file in os.listdir('./csse_covid_19_daily_reports_us')] , I have instead used files=[f for f in os.listdir("./") if f.endswith('.csv')] . This filtered out some garbage files that were not.csv, thus allowing me to compile all data into a single csv.