resampling

问题 I'm a newbie in python and using Dataframe from pandas package (python3.6). I set it up like below code, df = DataFrame({'list1': list1, 'list2': list2, 'list3': list3, 'list4': list4, 'list5': list5, 'list6': list6}) and it gives an error like ValueError: arrays must all be same length So I checked all the length of arrays, and list1 & list2 have 1 more data than other lists. If I want to add 1 data to those other 4 lists( list3 , list4 , list5 , list6 ) by using pd.resample , then how

问题 I am working on capturing and streaming audio to RTMP server at a moment. I work under MacOS (in Xcode), so for capturing audio sample-buffer I use AVFoundation-framework. But for encoding and streaming I need to use ffmpeg-API and libfaac encoder. So output format must be AAC (for supporting stream playback on iOS-devices). And I faced with such problem: audio-capturing device (in my case logitech camera) gives me sample-buffer with 512 LPCM samples, and I can select input sample-rate from

问题 I have a Yahoo finance daily stock price imported in a pandas dataframe. I want to use .resample() to convert it to the monthly stock price by taking the price of the first QUOTED daily price of each month. .resample('MS', how='first') returns the correct price of each month but it changes the index to the first day of the month while in general the first day of a month for a quoted price maybe 2nd or 3rd of the month because of holidays and weekends. How can I use resample() by only

问题 There are a couple similar questions on SO, but none of them really helped. Basically I am trying to resize a simple png image, as seen here: http://media.spiralknights.com/wiki-images/3/3e/Equipment-Proto_Sword_icon.png (from the mmo Spiral Knights, copyright Three Rings Entertainment) I had originally implemented a utility which uses these images in php, and the resizing utility there worked perfectly well. I used the method described on the imagecopyresampled page in PHP's documentation.

问题 Say I have a 10,000 pt vector that I want to take a slice of only 100 logarithmically spaced points. I want a function to give me integer values for the indices. Here's a simple solution that is simply using around + logspace, then getting rid of duplicates. def genLogSpace( array_size, num ): lspace = around(logspace(0,log10(array_size),num)).astype(uint64) return array(sorted(set(lspace.tolist())))-1 ls=genLogspace(1e4,100) print ls.size >>84 print ls array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,

问题 The application that I am trying to develop for andriod, records frames at 48Khz (PCM 16bits & mono) and sends them to the network. Also, there is an incoming stream of audio at 8Khz. So, I receive 8Khz sampled frames and play them (my AudioTrack object is set to 8Khz), but when playing them, everything works but the latency is HUGE. It takes like around 3 seconds until you hear something. I think that if I upsample the received frames from 8Khz to 48Khz and play them, there won't be such a

问题 I am using Pandas to structure and process Data. This is my DataFrame: I want to do a resampling of time-series data, and have, for every ID (named here "3"), all bitrate scores, from beginning to end (beginning_time / end_time). For exemple, for the first row, I want to have all seconds, from 2016-07-08 02:17:42 to 2016-07-08 02:17:55, with the same bitrate score, and the same ID of course. Something like this : For example, given : df = pd.DataFrame( {'Id' : ['CODI126640013.ts',

问题 I have a dataframe t_unit , which is the result of a pd.read_csv() function. datetime B18_LR_T B18_B1_T 24/03/2016 09:00 21.274 21.179 24/03/2016 10:00 19.987 19.868 24/03/2016 11:00 21.632 21.417 24/03/2016 12:00 26.285 24.779 24/03/2016 13:00 26.897 24.779 I am resampling the dataframe to calculate the 5th and 05th percentiles with the code: keys_actual = list(t_unit.columns.values) for key in keys_actual: ts_wk = t_unit[key].resample('W-MON') ts_wk_05p = ts_wk.apply(lambda x: x.quantile(0

问题 I'm looking for a pandas equivalent of the resample method for a dataframe whose isn't a DatetimeIndex but an array of integers, or maybe even floats. I know that for some cases (this one, for example) the resample method can be substituted easily by a reindex and interpolation, but for some cases (I think) it can't. For example, if I have df = pd.DataFrame(np.random.randn(10,2)) withdates = df.set_index(pd.date_range('2012-01-01', periods=10)) withdates.resample('5D', np.std) this gives me 0

问题 Dataframe.resample() works only with timeseries data. I cannot find a way of getting every nth row from non-timeseries data. What is the best method? 回答1: I'd use iloc , which takes a row/column slice, both based on integer position and following normal python syntax. df.iloc[::5, :] 回答2: Though @chrisb's accepted answer does answer the question, I would like to add to it the following. A simple method I use to get the nth data or drop the nth row is the following: df1 = df[df.index % 3 != 0]