CODEWITHSUNDEEP
pythonpandaslistdataframe
Jose
Jose

Reputation: 350

how to make a list from pandas if the index is timestamp

Here is my dataframe

ord_datetime
2019-05-01    22.483871
2019-05-02    27.228070
2019-05-03    30.140625
2019-05-04    32.581633
2019-05-05    30.259259

if i do code like this 

b=[]

b.append((df.iloc[2]-df.iloc[1])/(df.iloc[1]))

print(b)

output is 

[Ordered Items    0.106969
dtype: float64]

I want an output like 0.106969 only

How can i do that?

Upvotes: 2

Views: 352

Answers (3)

Eric
Eric

Reputation: 2729

You can do something like the following

import pandas as pd

data = {
    "ord_datetime": ["2019-05-01","2019-05-02","2019-05-03","2019-05-04","2019-05-05"],
    "value": [22.483871,27.228070,30.140625,32.581633,30.259259]
}

df = pd.DataFrame(data=data)

res = [ (df.iloc[ridx + 1, 1] - df.iloc[ ridx, 1]) / (df.iloc[ridx, 1]) for ridx in range(0, df.shape[0]-1) ]
res # [0.2110045463256749, 0.10696883767376833, 0.08098730533955406, -0.0712786249848188]

Hope it helps.

Upvotes: 1

Daniel Perez
Daniel Perez

Reputation: 6903

You are working with Series here, which is why you get this result. Your iloc returns a Series of 1 element, and the arithmetic operators also return series. If you want to get the scalar value, you can simply use my_series[0].

So for your example:

data = {datetime(2019, 5, 1): 22.483871, datetime(2019, 5, 2): 27.228070,
        datetime(2019, 5, 3): 30.140625, datetime(2019, 5, 4): 32.581633,
        datetime(2019, 5, 5): 30.259259}
df = pd.DataFrame.from_dict(data, orient="index")
series_result = (df.iloc[2] - df.iloc[1]) / df.iloc[1]
scalar_result = series_result[0]

# you can append the result to your list if you want

Upvotes: 1

Riley White
Riley White

Reputation: 53

If you want to just get the values from the output you can use df.values which returns a numpy array. If you want a list from that numpy array you can then use np_array.tolist.

So 

b = ((df.iloc[2]-df.iloc[1])/(df.iloc[1])).values #returns numpy array
b.tolist # returns python list

Upvotes: 0

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