Musi wa9 Ndira, Pandas 1.0.0rc yakaburitswa. Iyo yapfuura vhezheni yeraibhurari ndeye 0.25.

Yekutanga kuburitswa kukuru kune akawanda makuru maficha, anosanganisira yakagadziridzwa otomatiki dataframe muchidimbu, mamwe mafomati ekubuda, mhando dzedata nyowani, uye kunyange saiti nyowani yezvinyorwa.

Shanduko dzese dzinogona kutariswa pano, mune chinyorwa tichazviganhurira isu kudiki, kushoma kwehunyanzvi kuongorora kwezvinhu zvakakosha.

Unogona kuisa raibhurari semazuva ese uchishandisa Pip, asi kubvira panguva yekunyora Pandas 1.0 ichiri sunungura mumiriri, iwe uchafanirwa kutsanangura zvakajeka shanduro yacho:

pip install --upgrade pandas==1.0.0rc0

Ngwarira: sezvo uku kuri kuburitswa kukuru, iyo yekuvandudza inogona kutyora iyo yekare kodhi!

Nenzira, kutsigirwa kwePython 2 kwakamiswa zvachose kubvira iyi vhezheni (chingava chikonzero chakanaka update - approx. shanduro) Pandas 1.0 inoda kanenge Python 3.6+, saka kana usina chokwadi, tarisa kuti ndeipi yawakaisa:

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

$ python --version
Python 3.7.5

Nzira iri nyore yekutarisa iyo Pandas vhezheni ndeiyi:

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

Yakavandudzwa otomatiki-summarization neDataFrame.info

Chandaifarira innovation yaive yekuvandudza kune iyo nzira DataFrame.info. Basa racho rave kuverengeka zvakanyanya, zvichiita kuti maitiro ekutsvaga data ave nyore:

>>> 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

Kuburitsa matafura muMarkdown fomati

Iyo yakaenzana inonakidza innovation ndiko kugona kutumira dataframes kumatafura eMarkdown uchishandisa DataFrame.to_markdown.

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

Izvi zvinoita kuti zvive nyore kuburitsa matafura pamasaiti seMedium uchishandisa github gists.

Mhando itsva dzetambo uye booleans

Iyo Pandas 1.0 kuburitswa yakawedzerawo nyowani experimental mhando. API yavo inogona kuramba ichichinja, saka ishandise nekuchenjerera. Asi kazhinji, Pandas inokurudzira kushandisa mhando nyowani pese pazvine musoro.

Parizvino, kukanda kunofanira kuitwa zvakajeka:

>>> 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

Cherechedza kuti chikamu Dtype inoratidza mhando itsva − tambo и bool.

Chinhu chinonyanya kukosha chemhando itsva yetambo ndiko kukwanisa kusarudza mitsara mbiru chete kubva kune dataframes. Izvi zvinogona kuita kuti kupatsanura data yemavara kuve nyore:

df.select_dtypes("string")

Kare, mitsetse yaisagona kusarudzwa pasina kudoma mazita.

Iwe unogona kuverenga zvakawanda nezvemhando itsva pano.

Maita basa nekuverenga! Rondedzero yakazara yekuchinja, sezvatotaurwa, inogona kutariswa pano.

Source: www.habr.com