NgoJanuwari 9, iPandas 1.0.0rc yakhululwa. Inguqulo yangaphambilini yelabhulali ingu-0.25.

Ukukhishwa kokuqala okukhulu kuqukethe izici eziningi ezinhle ezintsha, okuhlanganisa ukufinyezwa kozimele bedatha okuzenzakalelayo okuthuthukisiwe, amafomethi amaningi okukhiphayo, izinhlobo ezintsha zedatha, kanye nesayithi elisha lemibhalo.

Zonke izinguquko zingabukwa lapha, esihlokweni sizozikhawulela ekubuyekezweni okuncane, okuncane kobuchwepheshe bezinto ezibaluleke kakhulu.

Ungafaka umtapo wolwazi njengokujwayelekile usebenzisa PIP, kodwa kusukela ngesikhathi sokubhala i-Pandas 1.0 namanje khulula ikhandidethi, uzodinga ukucacisa inguqulo:

pip install --upgrade pandas==1.0.0rc0

Qaphela: njengoba lokhu kuwukukhululwa okukhulu, isibuyekezo singase sephule ikhodi endala!

Ngendlela, ukusekelwa kwePython 2 kuyekwe ngokuphelele kusukela kule nguqulo (kungaba yini isizathu esihle buyekeza - cishe. ukuhumusha). I-Pandas 1.0 idinga okungenani i-Python 3.6+, ngakho-ke uma ungaqiniseki, hlola ukuthi iyiphi oyifakile:

$ pip --version
pip 19.3.1 from /usr/local/lib/python3.7/site-packages/pip (python 3.7)

$ python --version
Python 3.7.5

Indlela elula yokuhlola inguqulo yePandas yile:

>>> import pandas as pd
>>> pd.__version__
1.0.0rc0

Ukufinyezwa okuzenzakalelayo okuthuthukisiwe nge-DataFrame.info

Ukuqamba kwami ​​​​engikuthandayo kwakuyisibuyekezo sendlela IdathaFrame.info. Umsebenzi usufundeka kakhulu, okwenza inqubo yokuhlola idatha ibe lula nakakhulu:

>>> df = pd.DataFrame({
...:   'A': [1,2,3], 
...:   'B': ["goodbye", "cruel", "world"], 
...:   'C': [False, True, False]
...:})
>>> df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 3 entries, 0 to 2
Data columns (total 3 columns):
 #   Column  Non-Null Count  Dtype
---  ------  --------------  -----
 0   A       3 non-null      int64
 1   B       3 non-null      object
 2   C       3 non-null      object
dtypes: int64(1), object(2)
memory usage: 200.0+ bytes

Ikhipha amathebula ngefomethi ye-Markdown

Ukuqamba okusha okuhle ngokulinganayo yikhono lokuthekelisa ozimele bedatha kumathebula e-Markdown kusetshenziswa IdathaFrame.to_markdown.

>>> df.to_markdown()
|    |   A | B       | C     |
|---:|----:|:--------|:------|
|  0 |   1 | goodbye | False |
|  1 |   2 | cruel   | True  |
|  2 |   3 | world   | False |

Lokhu kwenza kube lula kakhulu ukushicilela amatafula kumasayithi afana ne-Medium usebenzisa i-github gists.

Izinhlobo ezintsha zezintambo nama-booleans

Ukukhishwa kwePandas 1.0 nakho kwengeze okusha okokuhlola izinhlobo. I-API yabo isengashintsha, ngakho-ke isebenzise ngokuqapha. Kodwa ngokuvamile, i-Pandas incoma ukusebenzisa izinhlobo ezintsha nomaphi lapho kunengqondo.

Okwamanje, ukulingisa kufanele kwenziwe ngokusobala:

>>> B = pd.Series(["goodbye", "cruel", "world"], dtype="string")
>>> C = pd.Series([False, True, False], dtype="bool")
>>> df.B = B, df.C = C
>>> df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 3 entries, 0 to 2
Data columns (total 3 columns):
 #   Column  Non-Null Count  Dtype
---  ------  --------------  -----
 0   A       3 non-null      int64
 1   B       3 non-null      string
 2   C       3 non-null      bool
dtypes: int64(1), object(1), string(1)
memory usage: 200.0+ bytes

Phawula ukuthi ikholomu kanjani Dtype ibonisa izinhlobo ezintsha − yezinhlamvu и bool.

Isici esisebenziseka kakhulu sohlobo olusha lweyunithi yezinhlamvu yikhono lokukhetha amakholomu emigqa kuphela kusuka kuma-dataframes. Lokhu kungenza ukuhlaziya idatha yombhalo kube lula kakhulu:

df.select_dtypes("string")

Ngaphambilini, amakholomu emigqa awakwazanga ukukhethwa ngaphandle kokucacisa ngokusobala amagama.

Ungafunda kabanzi mayelana nezinhlobo ezintsha lapha.

Siyabonga ngokufunda! Uhlu oluphelele lwezinguquko, njengoba selushiwo, lungabukwa lapha.

Source: www.habr.com