manipulating data in a DataFrame

 def get_price_history(stocks):           return df_of_colums    data_S = get_price_history("DIS")  pd.set_option("display.max_rows", None, "display.max_columns", None)    ##  how come this doesn't drop the columns?  data_S.drop(columns=['high', 'low'])    print(data_S[:10])  

This is what it prints:

     open      high     low   close      volume      datetime  0  145.54  146.0300  144.31  145.65   8268374.0  1.578290e+12  1  145.99  146.8699  145.42  145.70   6972813.0  1.578377e+12  2  145.49  146.1300  144.82  145.40   6986395.0  1.578463e+12  3  146.47  146.6250  144.61  144.83   6668201.0  1.578550e+12  4  145.30  145.5000  144.26  144.62   5154850.0  1.578636e+12  5  144.75  144.7500  143.36  143.88   9926387.0  1.578895e+12  6  143.41  146.7200  142.29  145.20  14846350.0  1.578982e+12  7  145.71  145.7100  143.93  144.32   6818180.0  1.579068e+12  8  145.09  145.4300  144.44  145.12   6948369.0  1.579154e+12  9  145.54  145.6400  144.01  144.33  10355328.0  1.579241e+12  

I also had a question about the difference in print statements. The way the grid works is that the bottom rows are the most recent trading data.

def count_gap_ups(data):     # data is the get_price_history     # data['open'].iloc[-254] this is how to get the last value     open_search_value = 251     close_search_value = 250     gap_up_count = 0     range_count =len(data_S)       for num in range(252):         open_value = data_S.iloc[open_search_value]["open"]         close_value = data_S.iloc[close_search_value]["close"]         if open_value > close_value:             gap_up_count += 1         open_value -= 1       close_search_value -= 1       return gap_up_count  print(str(count_gap_ups(data_S))+ " gap up count")  print(str(len(data_S))+ " length of data frame")  

Prints:

252 gap up count  252 length of data frame  

While the open price of row 2 is less than the close price of row 1.

Then when I change the number in range() like this.

ef count_gap_ups(data):  # data is the get_price_history  # data['open'].iloc[-254]  open_search_value = 251  close_search_value = 250  gap_up_count = 0  range_count =len(data_S)    for num in range(260):      open_value = data_S.iloc[open_search_value]["open"]      close_value = data_S.iloc[close_search_value]["close"]      if open_value > close_value:          gap_up_count += 1      open_value -= 1      close_search_value -= 1    return gap_up_count    print(str(count_gap_ups(data_S))+ " gap up count")  print(str(len(data_S))+ " length of data frame")  

Returns:

260 gap up count  252 length of data frame  

How come the for loop doesn't throw an error when there are no more rows to look at?

https://stackoverflow.com/questions/65589650/manipulating-data-in-a-dataframe January 06, 2021 at 11:03AM