data-science

问题 While I am importing the pandas in my data science project I am getting such kind of error. Does anyone know what might cause this? I tried with re-installation of pandas and python also I also tried with wheel import numpy as np import pandas as pd AttributeError Traceback (most recent call last) <ipython-input-2-b231533e2331> in <module> 1 import numpy as np ----> 2 import pandas as pd 3 from imblearn.over_sampling import SMOTE 4 from sklearn.model_selection import train_test_split 5 from

问题 I have cars,cities and routes. Every city is a node. Every route is a path generated by a car. Different cars will have different path, sometimes paths could be intersected (which means differents cars have found the same city in they path), sometimes not. I would rappresent a graph with all the cities and all the different path and plot the graph with plotly. Example: List of cities: CityA -CityB -CityD -CityZ -CityK List of cars: Car1, Car2 Routes: Car1 will have a path through cityA -

问题 I need to extract information about species and I write the following code. However, I have a problem with some absent species. How is it possible to avoid this problem. Q<-c("rvest","stringr","tidyverse","jsonlite") lapply(Q,require,character.only=TRUE) #This part was obtained by pagination that I not provided to have a short code sp1<-as.matrix(c("https://www.gulfbase.org/species/Acanthilia-intermedia", "https://www.gulfbase.org/species/Achelous-floridanus", "https://www.gulfbase.org

问题 Iam getting the error as "ValueError: Expected 2D array, got 1D array instead: array=[ 45000. 50000. 60000. 80000. 110000. 150000. 200000. 300000. 500000. 1000000.]. Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample." while executing the following code: # SVR # Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd # Importing the dataset dataset = pd.read_csv(

问题 I'd like to perform a hyperparameter search for selecting preprocessing steps and models in sklearn as follows: pipeline = Pipeline([("combiner", PolynomialFeatures()), ("dimred", PCA()), ("classifier", RandomForestClassifier())]) parameters = [{"combiner": [None]}, {"combiner": [PolynomialFeatures()], "combiner__degree": [2], "combiner__interaction_only": [False, True]}, {"dimred": [None]}, {"dimred": [PCA()], "dimred__n_components": [.95, .75]}, {"classifier": [RandomForestClassifier(n

问题 I have a data frame consists of column 1 i.e event and column 2 is Datetime: Sample data Event Time 0 2020-02-12 11:00:00 0 2020-02-12 11:30:00 2 2020-02-12 12:00:00 1 2020-02-12 12:30:00 0 2020-02-12 13:00:00 0 2020-02-12 13:30:00 0 2020-02-12 14:00:00 1 2020-02-12 14:30:00 0 2020-02-12 15:00:00 0 2020-02-12 15:30:00 And I want to find start time and end time of each event: Desired Data Event EventStartTime EventEndTime 0 2020-02-12 11:00:00 2020-02-12 12:00:00 2 2020-02-12 12:00:00 2020-02

问题 I have installed scikit-surprise in Windows10. C:\Users\Cosmos Lord>pip install scikit-surprise Requirement already satisfied: scikit-surprise in c:\users\cosmos lord\appdata\roaming\python\python37\site-packages (1.1.0) Requirement already satisfied: joblib>=0.11 in c:\users\cosmos lord\appdata\roaming\python\python37\site-packages (from scikit-surprise) (0.14.0) Requirement already satisfied: numpy>=1.11.2 in c:\users\cosmos lord\appdata\roaming\python\python37\site-packages (from scikit

问题 I am working on building a time series in R programming language. I m having a zoo object which is follows: I 'd like to convert this into a weekly time series data for analysis and typed in the following code tt2<-as.ts(zz,freq=365.25/7,start=decimal_date(ymd("2018-01-01"))) tt2[is.na(tt2)]<-0 However, I get the following output: Time Series: Start = 17538 End = 18532 Frequency = 0.142857142857143 While I'd like to see the output in line with something like this: Time Series: Start = c(2018

问题 I am working on building a time series in R programming language. I m having a zoo object which is follows: I 'd like to convert this into a weekly time series data for analysis and typed in the following code tt2<-as.ts(zz,freq=365.25/7,start=decimal_date(ymd("2018-01-01"))) tt2[is.na(tt2)]<-0 However, I get the following output: Time Series: Start = 17538 End = 18532 Frequency = 0.142857142857143 While I'd like to see the output in line with something like this: Time Series: Start = c(2018

问题 I am looking for a way to automatically (or as a shortcut) import a set of python modules in a jupyter notebook so that I don't have to import them every time I create a new notebook I am finding it very repetitive to import these modules to every notebook. The closest thing I could think here is creating a python file and importing that as a module, but I am looking for something more flexible in Jupyter-notebook # Example Code import pandas as pd import numpy as np import matplotlib.pyplot