Dynamically create names inside a dictionary using multiple variables

Question

There have been similar questions but I've not quite been able to get it right - apologies for duplications. What I would like to do is create dataframe names inside a dictionary based on variables as I iterate.

d = {}
market = 'SPX'
datatype = 'prices'

for j in range(10):
    year = 2010+j
    start = str(year) + '-01-01'
    end = str(year+2) + '-01-01'
        
    d['{market}_{datatype}_from_{start}_to{end}'] = 'foo'

I would like for the elements of the dictionary to be called

spx_prices_from_2010-01-01_to_2012-01-01
spx_prices_from_2011-01-01_to_2013-01-01
...

Thank you very much in advance

You have forgotten your string formatting. Change d['{market}_{datatype}_from_{start}_to{end}'] to d[f'{market}_{datatype}_from_{start}_to{end}'] — PacketLoss
– PacketLoss, Commented Mar 16, 2021 at 0:21

crcvd · Accepted Answer · 2021-03-16 00:27:01Z

2

If you're using Python 3, you can use f-strings:

d = {}
market = 'SPX'
datatype = 'prices'

for j in range(10):
    year = 2010+j
    start = str(year) + '-01-01'
    end = str(year+2) + '-01-01'
        
    d[f"{market}_{datatype}_from_{start}_to_{end}"] = 'foo'

Alternatively, you can use str's format method.

edited Mar 16, 2021 at 0:27

answered Mar 16, 2021 at 0:21

crcvd

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6 Comments

Tikhon Over a year ago

Woha that was easy. Thank you so much!!

Tikhon Over a year ago

1 more quick question if I haven't imposed too much already: is there an easy way of assigning the name of the dictionary itself - changing the name from d to "SPX_Prices" based on the variables?

crcvd Over a year ago

I'd avoid that and just use a collection (e.g. d['SPX']['prices'] = ...).

Tikhon Over a year ago

Thanks, but that doesn't do it... I think. I want to iterate through markets and datatypes - and for each create a dictionary of dataframes. So I want to name these dictionaries dynamically. Again, I'm super grateful

crcvd Over a year ago

The dictionaries will just be embedded in an outer dictionary. You can write: ``` for market in markets: for datatype in datatypes: d["{}_{}".format(market, datatypes)] = ... ``` You can then access all the dictionaries with d.values().

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