python

问题 I am doing the Alien Invasion project in the Python Crash Course book. When I test the code to see if the ship comes on screen the screen starts then shuts down. I have been looking through the code for hours now without finding out why. The game: import sys import pygame from settings import Settings from ship import Ship def run_game(): # Initialize pygame, settings, and screen object pygame.init() ai_settings = Settings() screen = pygame.display.set_mode( (ai_settings.screen_width, ai

问题 I am doing the Alien Invasion project in the Python Crash Course book. When I test the code to see if the ship comes on screen the screen starts then shuts down. I have been looking through the code for hours now without finding out why. The game: import sys import pygame from settings import Settings from ship import Ship def run_game(): # Initialize pygame, settings, and screen object pygame.init() ai_settings = Settings() screen = pygame.display.set_mode( (ai_settings.screen_width, ai

问题 I am doing the Alien Invasion project in the Python Crash Course book. When I test the code to see if the ship comes on screen the screen starts then shuts down. I have been looking through the code for hours now without finding out why. The game: import sys import pygame from settings import Settings from ship import Ship def run_game(): # Initialize pygame, settings, and screen object pygame.init() ai_settings = Settings() screen = pygame.display.set_mode( (ai_settings.screen_width, ai

问题 Assume that someone wants to package a Python (Cython) library that depends on the C++ boost library. What is the best way to configure the setup.py so that the user is properly informed that it is required to install the boost library (i.e., apt-get install libboost-dev in Ubuntu, etc in other OSes)? Or is it a better practice to include the boost library in the python package distribution? 回答1: The question is better asked as What is the best way to distribute a Python extension including

问题 I want to filter the rows of a dataframe that contains values less than ,say 10. import numpy as np import pandas as pd from pprint import pprint df = pd.DataFrame(np.random.randint(0,100,size=(10, 4)), columns=list('ABCD')) df = df[df <10] gives, A B C D 0 5.0 NaN NaN NaN 1 NaN NaN NaN NaN 2 0.0 NaN 6.0 NaN 3 NaN NaN NaN NaN 4 NaN NaN NaN NaN 5 6.0 NaN NaN NaN 6 NaN NaN NaN NaN 7 NaN NaN NaN 7.0 8 NaN NaN NaN NaN 9 NaN NaN NaN NaN Expected: 0 5 57 87 95 2 0 80 6 82 5 6 33 74 75 7 71 44 60 7

问题 I've got a dataframe with projects, start dates, and end dates. For each row I would like to return the number of other projects in process when the project started. How do you nest loops when using df.apply() ? I've tried using a for loop but my dataframe is large and it takes way too long. import datetime as dt data = {'project' :['A', 'B', 'C'], 'pr_start_date':[dt.datetime(2018, 9, 1), dt.datetime(2019, 4, 1), dt.datetime(2019, 6, 8)], 'pr_end_date': [dt.datetime(2019, 6, 15), dt.datetime

问题 I want to filter the rows of a dataframe that contains values less than ,say 10. import numpy as np import pandas as pd from pprint import pprint df = pd.DataFrame(np.random.randint(0,100,size=(10, 4)), columns=list('ABCD')) df = df[df <10] gives, A B C D 0 5.0 NaN NaN NaN 1 NaN NaN NaN NaN 2 0.0 NaN 6.0 NaN 3 NaN NaN NaN NaN 4 NaN NaN NaN NaN 5 6.0 NaN NaN NaN 6 NaN NaN NaN NaN 7 NaN NaN NaN 7.0 8 NaN NaN NaN NaN 9 NaN NaN NaN NaN Expected: 0 5 57 87 95 2 0 80 6 82 5 6 33 74 75 7 71 44 60 7

问题 I have several dataframes with identical shape/types, but slightly different numeric values. I can easily produce a new dataframe with the mean of all input dataframes via: df = pd.concat([input_dataframes]) df = df.groupby(df.index).mean() I want to do the same with harmonic mean (probably the scipy.stats.hmean function). I have attempted to do this using: .groupby(df.index).apply(scipy.stats.hmean) But this alters the structure of the dataframe. Is there a better way to do this, or do I

问题 I am trying to incorporate radio buttons in my form. In my forms.py I have the following fields for the form : class ProfileForm(forms.ModelForm): class Meta: model = Profile fields = ['first_name', 'last_name', 'gender'] In my models.py : user = models.ForeignKey(User, db_column='user_id') first_name = models.CharField(max_length=250) last_name = models.CharField(max_length=250 GENDER = (('M', 'Male'), ('F', 'Female'), ('O', 'Other')) gender = models.CharField(max_length=1, choices=GENDER,

问题 When sleeping for a long time (like running time.sleep(3**3**3) ) in Python 3, the program returns an OverflowError with the error message "timestamp too large to convert to C _PyTime_t". What is the largest time length I can sleep? 回答1: The value should be 9223372036.854775, which is "is the maximum value for a 64-bit signed integer in computing". See this Wikipedia article. Mentioning of _PyTime_t in PEP 564: The CPython private "pytime" C API handling time now uses a new _PyTime_t type: