Yahoo finance money converter

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These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience. Necessary Necessary. We applied it only to the Close column which contains the historical daily prices.

As a side note, it is worth mentioning that the forex market is a 24 hours market. So the close price time depends on the market where the observation is being taken.

Great, we can see that we have observations and that the mean value is 1. The highest value is 1. To know the date of this observation, we can use Pandas idmax function. Now that we have a Pandas dataframe with historical daily currency prices for the EURUSD pair, we can use matplotlib functionalities to visually see the trend:.

Before closing this post, I want to mention that to analyse the currency exposure experience in a company, we need to look into the company financial reports to get an idea of company sales currency exposure.

Once we have the currency mix exposure, we can look at the individual currencies by using what we have learned in this post.

We could apply the analysis performed in this post to understand how the currency was behaving in the past and determine how feasible is for this price pattern to repeat itself in the future.

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Turkmenistani new manat TMT. Ugandan shilling UGX. Ukrainian hryvnia UAH. Unidad de Fomento funds code CLF. Uruguayan peso UYU. Uzbekistani som UZS. Vanuatu vatu VUV.