Ka la 9 Pherekhong, Pandas 1.0.0rc e ile ea lokolloa. Mofuta o fetileng oa laebrari ke 0.25.
Tokollo ea pele e kholo e na le likarolo tse ngata tse ncha tse ncha, ho kenyelletsa kakaretso e ntlafalitsoeng ea dataframe, lifomate tse ngata tsa tlhahiso, mefuta e mecha ea data, esita le sebaka se secha sa litokomane.
Liphetoho tsohle li ka bonoa
U ka kenya laebrari joalo ka tloaelo u sebelisa pip, empa ho tloha ka nako ea ho ngola Pandas 1.0 e ntse e le teng mokhethoa ea lokollang, o tla hloka ho hlakisa mofuta ona:
pip install --upgrade pandas==1.0.0rc0
Ela hloko: kaha ena ke tokollo e kholo, ntlafatso e ka senya khoutu ea khale!
Ka tsela, ts'ehetso ea Python 2 e khaotsoe ka botlalo ho tloha phetolelong ena (seo e ka bang lebaka le letle
$ pip --version
pip 19.3.1 from /usr/local/lib/python3.7/site-packages/pip (python 3.7)
$ python --version
Python 3.7.5
Mokhoa o bonolo oa ho lekola mofuta oa Pandas ke ona:
>>> import pandas as pd
>>> pd.__version__
1.0.0rc0
Kakaretso e ntlafalitsoeng ea othomathike ka DataFrame.info
Ntho eo ke e ratang ka ho fetisisa e ne e le ho ntlafatsa mokhoa ona DataFrame.info. Ts'ebetso e se e ka baloa haholoanyane, e etsa hore mokhoa oa ho hlahloba data o be bonolo le ho feta:
>>> 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
Ho hlahisa litafole ka mokhoa oa Markdown
Boqapi bo monate ka ho tšoanang ke bokhoni ba ho romella li-dataframes ho litafole tsa Markdown u sebelisa DataFrame.to_markdown.
>>> df.to_markdown()
| | A | B | C |
|---:|----:|:--------|:------|
| 0 | 1 | goodbye | False |
| 1 | 2 | cruel | True |
| 2 | 3 | world | False |
Sena se etsa hore ho be bonolo haholo ho phatlalatsa litafole libakeng tse kang Medium ho sebelisa github gists.
Mefuta e mecha ea likhoele le li-booleans
Tokollo ea Pandas 1.0 e boetse e ekelitse e ncha tekolo mefuta. API ea bona e ntse e ka fetoha, kahoo e sebelise ka hloko. Empa ka kakaretso, Pandas e khothaletsa ho sebelisa mefuta e mecha hohle moo ho utloahalang.
Ho fihlela joale, mokhoa ona o lokela ho etsoa ka hloko:
>>> 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
Hlokomela kamoo kholomo Dtype e hlahisa mefuta e mecha − Khoele и bool.
Ntho ea bohlokoa ka ho fetisisa ea mofuta o mocha oa khoele ke bokhoni ba ho khetha litšiea tsa mela feela ho tsoa ho li-dataframes. Sena se ka nolofaletsa ho fetisa lintlha tsa mongolo:
df.select_dtypes("string")
Nakong e fetileng, mela e ne e sa khone ho khethoa ntle le ho hlalosa mabitso ka ho hlaka.
U ka bala ho eketsehileng ka mefuta e mecha
Kea leboha ha u bala! Lethathamo le felletseng la liphetoho, joalo ka ha ho boletsoe, le ka bonoa
Source: www.habr.com