pandas

问题 I have a dataframe which is basically several timeseries stacked on top of one another. Each time series has a unique label (group) and they have different date ranges. date = pd.to_datetime(pd.Series(['2010-01-01', '2010-01-02', '2010-01-03', '2010-01-06', '2010-01-01', '2010-01-03'])) group = [1,1,1,1, 2, 2] value = [1,2,3,4,5,6] df = pd.DataFrame({'date':date, 'group':group, 'value':value}) df date group value 0 2010-01-01 1 1 1 2010-01-02 1 2 2 2010-01-03 1 3 3 2010-01-06 1 4 4 2010-01-01

问题 I have a dataframe which is basically several timeseries stacked on top of one another. Each time series has a unique label (group) and they have different date ranges. date = pd.to_datetime(pd.Series(['2010-01-01', '2010-01-02', '2010-01-03', '2010-01-06', '2010-01-01', '2010-01-03'])) group = [1,1,1,1, 2, 2] value = [1,2,3,4,5,6] df = pd.DataFrame({'date':date, 'group':group, 'value':value}) df date group value 0 2010-01-01 1 1 1 2010-01-02 1 2 2 2010-01-03 1 3 3 2010-01-06 1 4 4 2010-01-01

问题 I'm trying to filter a dataframe based on the values within the multiple columns, based on a single condition, but keep other columns to which I don't want to apply the filter at all. I've reviewed these answers, with the third being the closest, but still no luck: how do you filter pandas dataframes by multiple columns Filtering multiple columns Pandas Python Pandas - How to filter multiple columns by one value Setup: import pandas as pd df = pd.DataFrame({ 'month':[1,1,1,2,2], 'a':['A','A',

问题 I am trying to convert a nested json array to a pandas data frame. The data looks something like this in list format: [{u'analysis': {u'active': u'Y', u'dpv_cmra': u'N', u'dpv_footnotes': u'AAN1', u'dpv_match_code': u'D', u'dpv_vacant': u'N', u'footnotes': u'H#'}, u'candidate_index': 0, u'components': {u'city_name': u'City', u'delivery_point': u'Variable', u'delivery_point_check_digit': u'8', u'plus4_code': u'Variable', u'primary_number': u'Variable', u'state_abbreviation': u'Variable', u

问题 I am trying to convert a nested json array to a pandas data frame. The data looks something like this in list format: [{u'analysis': {u'active': u'Y', u'dpv_cmra': u'N', u'dpv_footnotes': u'AAN1', u'dpv_match_code': u'D', u'dpv_vacant': u'N', u'footnotes': u'H#'}, u'candidate_index': 0, u'components': {u'city_name': u'City', u'delivery_point': u'Variable', u'delivery_point_check_digit': u'8', u'plus4_code': u'Variable', u'primary_number': u'Variable', u'state_abbreviation': u'Variable', u

问题 I have found the following method to downsample a signal in python. I would like to use this method with a sample_rate of 100.21 but I think currently it only works for integer powers of two. Is there a possibility to downsample my signal with frequency 100.21 Hz to 8 Hz? def interpolateDataTo8Hz(data,sample_rate,startTime): # Downsample idx_range = range(0,len(data)) data = data.iloc[idx_range[0::int(sample_rate)/8]] # Set the index to be 8Hz data.index = pd.DatetimeIndex(start=startTime

问题 What I have: df Name |Vehicle Dave |Car Mark |Bike Steve|Car Dave | Steve| I want to drop duplicates from the Name column but only if the corresponding value in Vehicle column is null. I know I can use df.dropduplicates(subset=['Name']) with either Keep = either 'First' or 'Last' but what I am looking for is a way to drop duplicates from Name column where the corresponding value of Vehicle column is null . So basically, keep the Name if the Vehicle column is NOT null and drop the rest. If a

问题 I am trying to learn pandas and want to load some stocks data. I was following a course which advised me to load pandas.io.data, but this did not work as io.data was depreciated. So I decided to use pandas-datareader instead. But I am struggling to instal it on mac in Anaconda (Jupiter notebook). First time I run import pandas_datareader as pdweb I got ModuleNotFoundError: No module named 'pandas_datareader'. Not surprising as I never used this before so I run pip3 install pandas_datareader

问题 I am trying to learn pandas and want to load some stocks data. I was following a course which advised me to load pandas.io.data, but this did not work as io.data was depreciated. So I decided to use pandas-datareader instead. But I am struggling to instal it on mac in Anaconda (Jupiter notebook). First time I run import pandas_datareader as pdweb I got ModuleNotFoundError: No module named 'pandas_datareader'. Not surprising as I never used this before so I run pip3 install pandas_datareader

问题 I am trying to learn pandas and want to load some stocks data. I was following a course which advised me to load pandas.io.data, but this did not work as io.data was depreciated. So I decided to use pandas-datareader instead. But I am struggling to instal it on mac in Anaconda (Jupiter notebook). First time I run import pandas_datareader as pdweb I got ModuleNotFoundError: No module named 'pandas_datareader'. Not surprising as I never used this before so I run pip3 install pandas_datareader