https://eric.nz/tags/python/ Recent content in python on Eric's Note https://eric.nz/%3Clink%20or%20path%20of%20image%20for%20opengraph,%20twitter-cards%3E https://eric.nz/%3Clink%20or%20path%20of%20image%20for%20opengraph,%20twitter-cards%3E Hugo -- gohugo.io Sat, 10 Oct 2020 13:31:15 +0000 https://eric.nz/posts/macos-uninstall-anaconda/ Sat, 10 Oct 2020 13:31:15 +0000 https://eric.nz/posts/macos-uninstall-anaconda/ Sometimes you need to re-config your local Anaconda environment, and need to uninstall Anaconda distribution completely. Automatic Uninstallation Step 1 Install the anaconda-clean package 1 conda install anaconda-clean Step 2 Clean your environment The anaconda-clean command will remove all Anaconda-related files and directories with a confirmation prompt before deleting each one. The --yes argument will help you to skip all confirmation and will remove all these files files and directories without confirmation. https://eric.nz/posts/py-pants/ Fri, 22 Mar 2019 12:58:35 +0000 https://eric.nz/posts/py-pants/ Reference Pants Official document Getting started with Pants https://eric.nz/posts/py-pandas-best-practice/ Fri, 01 Mar 2019 12:58:35 +0000 https://eric.nz/posts/py-pandas-best-practice/ Data Manipulation Dedup DataFrame Sometimes we want to drop all the duplicated data in our DataFrame, and we can use the drop_duplicates() function. For Example: 1 2 3 4 5 6 7 8 9 10 11 12 df = pd.DataFrame({ 'brand': ['Yum Yum', 'Yum Yum', 'Indomie', 'Indomie', 'Indomie'], 'style': ['cup', 'cup', 'cup', 'pack', 'pack'], 'rating': [4, 4, 3.5, 15, 5] }) df brand style rating 0 Yum Yum cup 4.0 1 Yum Yum cup 4. https://eric.nz/posts/py-pandas-basic-usage/ Sat, 06 Oct 2018 21:54:03 +0000 https://eric.nz/posts/py-pandas-basic-usage/ DataFrame Create a DataFrame Get DataFrame Column Headers list(df) Reference RealPython.com: Python Pandas: Tricks & Features You May Not Know TowardDataScience.com: 23 great Pandas codes for Data Scientists Analyticsvidhya.com: 12 Useful Pandas Techniques in Python for Data Manipulation https://eric.nz/posts/py-pipenv/ Thu, 03 Dec 2015 03:41:32 +0000 https://eric.nz/posts/py-pipenv/ General Pipenv is a packaging tool for Python that solves some common problems associated with the typical workflow using pip, virtualenv, and requirements.txt. Pipenv is designed to resolve dependency management chaos created by requirements.txt. Introduction First, let’s install the pipenv package. Pipenv uses pip and virtualenv under the hood but simplifies their usage with a single command-line interface. 1 pip install --user pipenv Pipenv introduces two new files. Pipfile is to replace the old requirements. https://eric.nz/posts/py-type-hint/ Thu, 03 Dec 2015 03:41:32 +0000 https://eric.nz/posts/py-type-hint/ Bad Code 1 2 3 4 5 6 7 def get_authors_names(posts): authors_names = [] for post in posts: author = post["author"] author_name = author["name"] authors_names.append(author_name) return authors_names Good code 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 from typing import List, TypedDict class Author(TypedDict): name: str email: str bio: str website: str class Post(TypeDict): title: str author: Author publication_date: str content: str def get_authors_names(posts: List[Post]) -> List[str]: return [post["author"]["name"] for post in posts] https://eric.nz/posts/py-library/ Fri, 06 Mar 2015 03:06:35 +0000 https://eric.nz/posts/py-library/ Stats & exploratory analysis Numpy. Pandas. SciPy. Statsmodels. Patsy. Emcee. Machine Learning Scikit-learn. TensorFlow. Keras. Theano. Lifelines. Data Visualization Matplotlib. Plotly. Seaborn. Geomap. Folium. Networkx. Basemap. Web Scraping BeautifulSoup. ScraPy. Requests. Natural Language Processing NLTK. Gensim. TextBlob. Utility when-changed. tenacity .