I am having trouble with some of pandas functionalities. How do I check what is my installation version?
6 Answers
Check pandas.__version__:
In [76]: import pandas as pd In [77]: pd.__version__ Out[77]: '0.12.0-933-g281dc4e' Pandas also provides a utility function, pd.show_versions(), which reports the version of its dependencies as well:
In [53]: pd.show_versions(as_json=False) INSTALLED VERSIONS ------------------ commit: None python: 2.7.6.final.0 python-bits: 64 OS: Linux OS-release: 3.13.0-45-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 pandas: 0.15.2-113-g5531341 nose: 1.3.1 Cython: 0.21.1 numpy: 1.8.2 scipy: 0.14.0.dev-371b4ff statsmodels: 0.6.0.dev-a738b4f IPython: 2.0.0-dev sphinx: 1.2.2 patsy: 0.3.0 dateutil: 1.5 pytz: 2012c bottleneck: None tables: 3.1.1 numexpr: 2.2.2 matplotlib: 1.4.2 openpyxl: None xlrd: 0.9.3 xlwt: 0.7.5 xlsxwriter: None lxml: 3.3.3 bs4: 4.3.2 html5lib: 0.999 httplib2: 0.8 apiclient: None rpy2: 2.5.5 sqlalchemy: 0.9.8 pymysql: None psycopg2: 2.4.5 (dt dec mx pq3 ext) Run:
pip list You should get a list of packages (including pandas) and their versions, e.g.:
beautifulsoup4 (4.5.1) cycler (0.10.0) jdcal (1.3) matplotlib (1.5.3) numpy (1.11.1) openpyxl (2.2.0b1) pandas (0.18.1) pip (8.1.2) pyparsing (2.1.9) python-dateutil (2.2) python-nmap (0.6.1) pytz (2016.6.1) requests (2.11.1) setuptools (20.10.1) six (1.10.0) SQLAlchemy (1.0.15) xlrd (1.0.0) Simplest Solution
Code:
import pandas as pd pd.__version__ **Its double underscore before and after the word "version".
Output:
'0.14.1' Run
pip freeze It works the same as above.
pip show pandas Displays information about a specific package. For more information, check out pip help
Windows
python -c "import pandas as pd; print(pd.__version__)" conda list | findstr pandas # Anaconda / Conda pip freeze | findstr pandas pip show pandas | findstr Version Linux
python -c "import pandas as pd; print(pd.__version__)" conda list | grep numpy # Anaconda / Conda pip freeze | grep numpy # pip In a jupyter notebook cell: pip freeze | grep pandas 
