CODEWITHSUNDEEP
pythonpandasdataframe
Sociopath
Sociopath

Reputation: 13426

How to use previous values from Dataframe in if statement

I have DataFrame df

df=pd.DataFrame([[47,55,47,50], [33,37,30,25],[61,65,54,57],[25,26,21,22], [25,29,23,28]], columns=['open','high','low','close'])

print(df)

    open    high    low     close
0   47      55      47      50
1   33      37      30      25
2   61      65      54      57
3   25      26      21      22
4   25      29      23      20

I want to use previous values in if statement to compare. Logic is as below:

 if (close[i-1]/close[i] > 2) and (high[i] < low[i-1]) and 
((open[i] > high[i-1]) or (open[i] <low[i-1])) :

I have written a code :

for idx,i in df.iterrows():
    if idx !=0 :
        if ((prv_close/i['close'])>2) and (i['high'] < prv_low) and ((i['open'] > prv_high) or (i['open'] < prv_low)):
            print("Successful")
        else: 
            print("Not Successful")

    prv_close = i['close']
    prv_open = i['open']
    prv_low = i['low']
    prv_high = i['high']

output:

Not Successful
Not Successful
Successful
Not Successful

But For millions of rows it's taking too much time. Is there any other way to implement it faster?

P.S : Action to be taken on data are different in if statement. For simplicity I'm using print statement. My columns may not have same order this is why I'm using iterrows() instead of itertuples().

Any suggestions are welcome. Thanks.

Upvotes: 1

Views: 47

Answers (1)

piRSquared
piRSquared

Reputation: 294586

d0 = df.shift()

cond0 = (d0.close / df.close) > 2
cond1 = df.high < d0.low
cond2 = df.open > d0.high
cond3 = df.open < d0.low

mask = cond0 & cond1 & (cond2 | cond3)

mask

0    False
1    False
2    False
3     True
4    False
dtype: bool

Upvotes: 1

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