"df = pd.read_csv('xxx.csv')" resets the date format in my csv file

In my csv file, I save my dates in this format: "yyyy-mm-dd". Every time I pull the data from csv and into a pandas dataframe, it will reset the format to "yyyy/mm/dd" in my csv file. This will cause errors if I test my code again, so I have to open the csv and reformat the date column to yyyy-mm-dd again.

Do you know why CSV does this? Is there a permanent solution to make sure my date format doesn't reset every time pandas reads my csv file?

Here is some of my code directly related to reading my csv file:

origindf = pd.read_csv('testlist.csv')
origindf = pd.DataFrame(origindf, columns=["ticker","date"])
origintickers = origindf['ticker'].values.tolist()
origintickersiterate = origindf['ticker'].values.tolist()
origindates = origindf['date'].values.tolist()

masterdf = pd.DataFrame(columns = ['ticker', 'date', 'time', 'vol', 'vwap', 'open', 'high', 'low','close','trades'])

for ticker in origintickersiterate:
    polygonapi = 'xxxxxxxxxxxxxxx'
    limit = 10000
    multiplier = 1
    timespan = 'minute'
    adjusted = 'False'
    theticker = origintickers.pop()
    thedate = origindates.pop()

Assuming that pandas recognises the original text as dates, it will represent it as datetime64[ns] which is not text and how it displays on screen, eg with df.head() is irrelevant. You can check the data formats with df.dtypes to make sure.

Pandas to_csv allows you to control the format of the output dates with the date_format parameter, eg:

df.to_csv('testlist.csv', date_format='%Y-%m-%d')

I suggest viewing the output in a text editor because Excel will parse the dates and may convert them.

Current documentation: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_csv.html