Ni Oṣu Kini Ọjọ 9, Pandas 1.0.0rc ti tu silẹ. Ẹya ti tẹlẹ ti ile-ikawe jẹ 0.25.
Itusilẹ pataki akọkọ ni ọpọlọpọ awọn ẹya tuntun nla, pẹlu imudara akopọ dataframe adaṣe, awọn ọna kika diẹ sii, awọn iru data tuntun, ati paapaa aaye iwe aṣẹ tuntun kan.
Gbogbo awọn ayipada le ṣee wo
O le fi awọn ìkàwé bi ibùgbé lilo Pipa, sugbon niwon ni akoko kikọ Pandas 1.0 jẹ ṣi oludije tu silẹ, iwọ yoo nilo lati pato ẹya naa ni gbangba:
pip install --upgrade pandas==1.0.0rc0
Ṣọra: nitori eyi jẹ itusilẹ pataki, imudojuiwọn le fọ koodu atijọ!
Nipa ọna, atilẹyin fun Python 2 ti dawọ patapata lati ẹya yii (ohun ti o le jẹ kan ti o dara idi
$ pip --version
pip 19.3.1 from /usr/local/lib/python3.7/site-packages/pip (python 3.7)
$ python --version
Python 3.7.5
Ọna to rọọrun lati ṣayẹwo ẹya Pandas ni eyi:
>>> import pandas as pd
>>> pd.__version__
1.0.0rc0
Imudara akopọ adaṣe pẹlu DataFrame.info
Ayanfẹ mi ĭdàsĭlẹ wà imudojuiwọn si ọna DataFrame.info. Iṣẹ naa ti di kika pupọ diẹ sii, ṣiṣe ilana ti iṣawari data paapaa rọrun:
>>> 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
Awọn tabili ti njade ni ọna kika Markdown
Iṣe tuntun ti o dun deede ni agbara lati okeere dataframes si awọn tabili Markdown nipa lilo DataFrame.to_markdown.
>>> df.to_markdown()
| | A | B | C |
|---:|----:|:--------|:------|
| 0 | 1 | goodbye | False |
| 1 | 2 | cruel | True |
| 2 | 3 | world | False |
Eyi jẹ ki o rọrun pupọ lati ṣe atẹjade awọn tabili lori awọn aaye bii Alabọde ni lilo awọn github gists.
Awọn oriṣi tuntun fun awọn okun ati awọn booleans
Itusilẹ Pandas 1.0 tun ṣafikun tuntun esiperimenta orisi. API wọn le tun yipada, nitorinaa lo pẹlu iṣọra. Ṣugbọn ni gbogbogbo, Pandas ṣeduro lilo awọn iru tuntun nibikibi ti o jẹ oye.
Ni bayi, simẹnti nilo lati ṣe ni gbangba:
>>> 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
Ṣe akiyesi bi ọwọn naa Dtype han titun orisi - okun и ọdẹ.
Ẹya ti o wulo julọ ti iru okun tuntun ni yiyan nikan kana ọwọn lati awọn fireemu data. Eyi le jẹ ki sisọ data ọrọ rọrun pupọ:
df.select_dtypes("string")
Ni iṣaaju, awọn ọwọn ila ko le yan laisi awọn orukọ ni pato.
O le ka diẹ ẹ sii nipa titun orisi
O ṣeun fun kika! Akojọ kikun ti awọn ayipada, bi a ti sọ tẹlẹ, le wo
orisun: www.habr.com