Python: replace columns using dictionary

I have a DataFrame that looks like this:

df:
date        price region        currency
2022-01-01  1     NorthAmerica  UnitedStatesDollar
2022-01-01  1.28  NorthAmerica  CanadianDollar
2022-01-01  1.42  Oceania       AustralianDollar
2022-01-02  1     NorthAmerica  UnitedStatesDollar
2022-01-02  1.29  NorthAmerica  CanadianDollar
2022-01-02  1.41  Oceania       AustralianDollar

I have a dictionary as follows:

currency_dict = [
  {
    'symbol': 'USD',
    'region': 'NorthAmerica',
    'currency': 'UnitedStatesDollar',
  },
  {
    'symbol': 'CAD',
    'region': 'NorthAmerica',
    'currency': 'CanadianDollar',
  },
  {
    'symbol': 'AUD',
    'region': 'Oceania',
    'currency': 'AustralianDollar',
  },
];

I want to use the dictionary to get the following DataFrame:

df:
date        price  symbol
2022-01-01  1      USD
2022-01-01  1.28   CAD
2022-01-01  1.42   AUD
2022-01-02  1      USD
2022-01-02  1.29   CAD
2022-01-02  1.41   AUD

I have tried df.replace(currency_dict, inplace=True) but I am not sure how that would work with replacing two columns.

Thank you in advance.

EDIT: This is a list of dictionaries! Thanks for all the comments

>Solution :

Another example:

df_currency = pd.DataFrame(currency_dict) # currency_dict actually a list of dict!!
result = pd.merge(df, df_currency)[['date', 'price', 'symbol']]

References:

https://realpython.com/pandas-merge-join-and-concat/

https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#database-style-dataframe-or-named-series-joining-merging