CODEWITHSUNDEEP
pandas
D S
D S

Reputation: 1

pandas timeseries condition met show next few rows

I have a pandas dataframe loaded with end of day data for AAPL from Yahoo Finance. I'm looking for a certain condition in the data to meet (say, when close of a day is near the lows of the day) and after which (say, on 2012-01-01 the condition was met), I would like to immediately see the next few rows (I'm interested in the closing price of AAPL on 2012-01-02 and 2012-01-03 and so on).

I used dataframe query which results in just the row where the condition was matched. I don't know how to extract the rows immediately following the matched condition row.

How do I go about accomplishing this? Is "query" the wrong method?

Thank you, D

Upvotes: 0

Views: 24

Answers (1)

fuglede
fuglede

Reputation: 18201

Do you know that you'll have exactly one result? Then you can get them more or less by hand as follows:

In [44]: df  # Example DataFrame
Out[44]: 
  c1  c2
0  a   5
1  b  10
2  c  15

In [45]: index = df[df['c1'] == 'b'].index[0]  # Get the index of the row of interest.

In [47]: df.iloc[range(index, index + 2)]  # Get that row and whatever follows immediately after
Out[47]: 
  c1  c2
1  b  10
2  c  15

If you have more than one result, iterate over df[df['c1'] == 'b'].index instead.

Upvotes: 1

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