Muchikamu chino, tichaongorora maitiro ekuwedzera koramu nyowani kuPandas DataFrame, raibhurari yakakurumbira muPython yekunyengedza data uye kuongorora. Isu tichakurukura mhinduro yedambudziko iri, pfuura-nhanho-nhanho tsananguro yekodhi, uye tivhare mamwe ane hukama misoro uye mabasa muPandas raibhurari. Pandas iraibhurari inoshandiswa-inoshandiswa zvakanyanya ine yakakwirira-level data zvimiro uye maturusi, akakwana pakunyatsoongorora data uye kubata mabasa.
Kutanga, ngatifungei isu tine dhatabheti muchimiro chePandas DataFrame uye tinoda kuwedzera koromo itsva kwairi. Ichi chinhu chinowanzo diwa mudanho rekugadzirira data, rinowanzodikanwa kune chimiro cheinjiniya kana kugadzira rumwe ruzivo rwakavakirwa pamakoramu aripo. Ngatinyure mukuti izvi zvingawanikwe sei.
Kuwedzera chinyorwa chitsva kune Pandas DataFrame
Tichatanga nekupinza raibhurari inodiwa uye kugadzira sampuli DataFrame.
import pandas as pd
data = {'Name': ['Alex', 'Tom', 'Nick', 'Sam'],
'Age': [25, 28, 23, 22],
'City': ['NY', 'LA', 'SF', 'Chicago']}
df = pd.DataFrame(data)
Ikozvino, ngatiwedzerei nyowani nyowani 'Nyika' kune yedu DataFrame ine default kukosha, iti 'USA'.
df['Country'] = 'USA'
Uyu mutsara wakapfava wekodhi uchawedzera koramu itsva inonzi 'Nyika' kune yedu iripo DataFrame 'df' ine kukosha 'USA' mumitsara yayo yese. Yedu yakagadziridzwa DataFrame yaizotaridzika seizvi:
Name Age City Country 0 Alex 25 NY USA 1 Tom 28 LA USA 2 Nick 23 SF USA 3 Sam 22 Chicago USA
Nhanho-ne-nhanho kodhi tsananguro
Ngatiparadze kodhi uye tinzwisise nhanho nhanho.
1. Chekutanga, tinopinza raibhurari yePandas tichishandisa yakajairwa alias 'pd'. Izvi zvinotibvumira kuwana mabasa ePandas uye makirasi tichishandisa 'pd' prefix.
import pandas as pd
2. Zvadaro, tinogadzira duramazwi 'data' rine imwe data data. Kiyi imwe neimwe muduramazwi inomiririra zita rekoramu, uye kukosha kwaro kunoenderana nerondedzero yezvakakosha zvekoramu iyoyo.
data = {'Name': ['Alex', 'Tom', 'Nick', 'Sam'],
'Age': [25, 28, 23, 22],
'City': ['NY', 'LA', 'SF', 'Chicago']}
3. Tinozoshandura duramazwi iri kuita Pandas DataFrame chinhu tichishandisa `pd.DataFrame()` basa.
df = pd.DataFrame(data)
4. Pakupedzisira, kuwedzera mutsara mutsva, tinongoshandisa mushandisi webasa "=" neDataFrame, tichipa zita idzva rekoramu mukati memabhuraketi akaenzana uye tichitsanangura kukosha kwekugadziriswa. Kwatiri isu, isu takawedzera iyo 'Nyika' koramu ine default kukosha 'USA'.
df['Country'] = 'USA'
Pandas raibhurari uye mabasa anoenderana
Pandas ine simba Python raibhurari, kunyanya yakakodzera kugadzirisa data, kuchenesa uye kuongorora mabasa. Inopa maviri makuru data zvimiro: DataFrame uye Series. A DataFrame imbiri-dimensional tabular data dhizaini ine axes akanyorwa (mitsara nemakoramu). A Series, kune rumwe rutivi, ndeye-dimensional yakanyorwa array inokwanisa kubata data yechero mhando.
Mamwe mabasa akajairika ePandas ane chekuita nekuwedzera, kugadzirisa uye kudzima makoramu muDataFrame ndeaya anotevera:
- kuisa(): Kuisa koramu panzvimbo yakatarwa.
- Donhedza(): Kubvisa koramu kubva kuDataFrame.
- rename(): Kutumidza zita reDataFrame's column.
- assign(): Kugadzira koramu itsva zvichienderana nemhedzisiro yeshoko.
Saka, kuwedzera koramu nyowani kuPandas DataFrame iri nyore uye inoshanda. Muchinyorwa chino, takafukidza nzira yekutanga yekuwedzera koramu nyowani ine default kukosha uye nekupa tsanangudzo dzakadzama dzematanho anobatanidzwa. Isu takaunzawo Pandas seraibhurari ine simba rekushandisa data uye takakurukura mamwe mabasa ane hukama ekutarisira DataFrame makoramu. Nekugona aya matekiniki, iwe unenge wakashongedzerwa zvakakwana kubata akasiyana siyana ekugadzirisa data mabasa muPython.
