Python: Pandas dataframe to call a value

Question

I convert json to Pandas dataframe and would like to call the value of "c".

>>> quote
{u'c': 89.77, u'h': 90.51, u'l': 89.32, u'o': 90.09, u'pc': 90.29, u't': 1591778794}
>>> quote = pd.DataFrame(quote.items())
>>> quote
    0             1
0   c  8.977000e+01
1   h  9.051000e+01
2   l  8.932000e+01
3   o  9.009000e+01
4  pc  9.029000e+01
5   t  1.591779e+09

I want the data for c. I currently used quote.iloc[0][1] but it is not robust. What is the robust and elegant way to get the data for "c"?

quote[quote['0'] == 'c'] should probably work. This way you can get the sub-dataframe where the value of column '0' is 'c' (regardless of its position). — geoph9
– geoph9, Commented Jun 10, 2020 at 8:56

keepAlive · Accepted Answer · 2020-06-10 09:19:19Z

With quote_items and wanted such as

quote_items = {
    u'c': 89.77,
    u'h': 90.51,
    u'l': 89.32,
    u'o': 90.09,
    u'pc': 90.29,
    u't': 1591778794
}.items()

wanted = 'c'

What about simply setting as index the first column, i.e.

>>> df = pd.DataFrame(quote_items).set_index(0)
>>> df.loc[wanted]
1    89.77
Name: c, dtype: float64

Or even dealing with the transpose to make things shorter

>>> df = pd.DataFrame(quote_items).set_index(0).T
>>> df[wanted]  # <=> df.loc[:, wanted]
1    89.77
Name: c, dtype: float64

Otherwise, if you do not want to locate your data, what follows may be enough

>>> df = pd.DataFrame(quote_items)
>>> df[df[0]==wanted]
   0      1
0  c  89.77

less readable IMHO, and not ending with the same type of object (pd.DataFrame instead of pd.Series as previously)

But in the first place: is your input dictionary really representative of the data you have to deal with ? Depending on that, our answers may vary.

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