pandas

问题 I am trying to store the results of FFT calculations in a Pandas data frame: ft = pd.DataFrame(index=range(90)) ft['y'] = ft.index.map(lambda x: np.sin(2*x)) ft['spectrum'] = np.fft.fft(ft['y']) ft['freq'] = np.fft.fftfreq(len(ft.index)).real ft['T'] = ft['freq'].apply(lambda f: 1/f if f != 0 else 0) Everything seems to be working fine until the last line: the column T which is supposed to store periods has for some reason all the columns of the frame, ie.: In [499]: ft.T[0] Out[499]: y 0j

问题 I am trying to store the results of FFT calculations in a Pandas data frame: ft = pd.DataFrame(index=range(90)) ft['y'] = ft.index.map(lambda x: np.sin(2*x)) ft['spectrum'] = np.fft.fft(ft['y']) ft['freq'] = np.fft.fftfreq(len(ft.index)).real ft['T'] = ft['freq'].apply(lambda f: 1/f if f != 0 else 0) Everything seems to be working fine until the last line: the column T which is supposed to store periods has for some reason all the columns of the frame, ie.: In [499]: ft.T[0] Out[499]: y 0j

问题 I am trying to scrape Naukri job postings. Web scraping was too time-consuming, so I switched to network requests. I believe I got the request pattern for pagination by changing the URL right (not clicking the next tab). URLs Example: https://www.naukri.com/maintenance-jobs?xt=catsrch&qf%5B%5D=19 https://www.naukri.com/maintenance-jobs-2?xt=catsrch&qf%5B%5D=19 https://www.naukri.com/maintenance-jobs-3?xt=catsrch&qf%5B%5D=19 https://www.naukri.com/maintenance-jobs-4?xt=catsrch&qf%5B%5D=19 The

问题 I am trying to scrape Naukri job postings. Web scraping was too time-consuming, so I switched to network requests. I believe I got the request pattern for pagination by changing the URL right (not clicking the next tab). URLs Example: https://www.naukri.com/maintenance-jobs?xt=catsrch&qf%5B%5D=19 https://www.naukri.com/maintenance-jobs-2?xt=catsrch&qf%5B%5D=19 https://www.naukri.com/maintenance-jobs-3?xt=catsrch&qf%5B%5D=19 https://www.naukri.com/maintenance-jobs-4?xt=catsrch&qf%5B%5D=19 The

问题 Having problems with the .dropna() method. I have created a new variable energy_c which is a copy of energy but with mont being more or equal to 0.1 . I then took out the columns with nothing in after printing them and then am trying to drop all rows that have NaN values in the remaining columns. However my output is returning NaN values even after using .dropna() . energy_c = energy.loc[energy.loc[:, 'mont'] >= 0.1].copy() energy_c.columns[energy.isna().all()].tolist() drop_cols = energy_c

问题 I have a df like this: A | B | C | D 14 | 5 | 10 | 5 4 | 7 | 15 | 6 100 | 220 | 6 | 7 For each row in column A,B,C, I want the find the max value and from it subtract column D and replace it. Expected result: A | B | C | D 9 | 5 | 10 | 5 4 | 7 | 9 | 6 100 | 213 | 6 | 7 So for the first row, it would select 14(the max out of 14,5,10), subtract column D from it (14-5 =9) and replace the result(replace initial value 14 with 9) I know how to find the max value of A,B,C and from it subctract D,

问题 I have a df like this: A | B | C | D 14 | 5 | 10 | 5 4 | 7 | 15 | 6 100 | 220 | 6 | 7 For each row in column A,B,C, I want the find the max value and from it subtract column D and replace it. Expected result: A | B | C | D 9 | 5 | 10 | 5 4 | 7 | 9 | 6 100 | 213 | 6 | 7 So for the first row, it would select 14(the max out of 14,5,10), subtract column D from it (14-5 =9) and replace the result(replace initial value 14 with 9) I know how to find the max value of A,B,C and from it subctract D,

问题 I do the following operations: Convert string datetime in pandas dataframe to python datetime via apply(strptime) Convert datetime to posix timestamp via .timestamp() method If I revert posix back to datetime with .fromtimestamp() I obtain different datetime It differs by 3 hours which is my timezone (I'm at UTC+3 now), so I suppose it is a kind of timezone issue. Also I understand that in apply it implicitly converts to pandas.Timestamp , but I don't understand the difference in this case.

问题 I want to cut one column in my pandas.DataFrame using pandas.cut(), but the labels I put into labels argument are not applied. Let me show you an example. I have got the following data frame: >>> import pandas as pd >>> df = pd.DataFrame({'x': [-0.009, 0.089, 0.095, 0.096, 0.198]}) >>> print(df) x 0 -0.009 1 0.089 2 0.095 3 0.096 4 0.198 And I cut x column like this: >>> bins = pd.IntervalIndex.from_tuples([(-0.2, -0.1), (-0.1, 0.0), (0.0, 0.1), (0.1, 0.2)]) >>> labels = [100, 200, 300, 400]

问题 I do the following operations: Convert string datetime in pandas dataframe to python datetime via apply(strptime) Convert datetime to posix timestamp via .timestamp() method If I revert posix back to datetime with .fromtimestamp() I obtain different datetime It differs by 3 hours which is my timezone (I'm at UTC+3 now), so I suppose it is a kind of timezone issue. Also I understand that in apply it implicitly converts to pandas.Timestamp , but I don't understand the difference in this case.