Here is my dataset
Date,p1Close,p2Close, spread, movingAverage
2022-02-28,5,10,2,NaN
2022-03-01,2,6,3,2.5
2022-03-02,4,8,2,2,5
2022-03-03,2,8,4,3
I am trying to create a new column in pandas data frame that is equal to the standard deviation between 'spread' from previous row and current row.
df['standardDeviation'] = statistics.stdev(df['spread'], df['spread'].shift(1))
I keep getting this error:
File "/usr/lib/python3.9/statistics.py", line 797, in stdev
var = variance(data, xbar)
File "/usr/lib/python3.9/statistics.py", line 740, in variance
T, ss = _ss(data, xbar)
File "/usr/lib/python3.9/statistics.py", line 684, in _ss
T, total, count = _sum((x-c)**2 for x in data)
File "/usr/lib/python3.9/statistics.py", line 166, in _sum
for n, d in map(_exact_ratio, values):
File "/usr/lib/python3.9/statistics.py", line 248, in _exact_ratio
raise TypeError(msg.format(type(x).__name__))
TypeError: can't convert type 'Series' to numerator/denominator
I believe it is because I am using shift(1) and on the first calculation it doesn't have a shift(1) value so it errors out. Not sure how to approach solving this one.
CodePudding user response:
You can actually just use <column>.rolling(2).std()
:
df['standardDeviation'] = df['spread'].rolling(2).std()
Output:
>>> df
Date p1Close p2Close spread movingAverage standardDeviation
0 2022-02-28 5 10 2 NaN NaN
1 2022-03-01 2 6 3 2.5 0.707107
2 2022-03-02 4 8 2 2.0 0.707107
3 2022-03-03 2 8 4 3.0 1.414214
CodePudding user response:
@richardec's answer is the best solution but for your specific question, statistics.stdev
expects an iterator, so you'll need to pass in pairs:
df['stdev'] = [statistics.stdev(pair) for pair in zip(df['spread'], df['spread'].shift())]
Output:
Date p1Close p2Close spread movingAverage stdev
0 2022-02-28 5 10 2 NaN NaN
1 2022-03-01 2 6 3 2.5 0.707107
2 2022-03-02 4 8 2 2.0 0.707107
3 2022-03-03 2 8 4 3.0 1.414214