Converti Panda in Excel
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Utilizzando Aspose.Cells for Python via .NET API, puoi convertire Panda DataFrame in Excel, OpenOffice, Pdf, Json e molti formati diversi.
Converti Pandas DataFrame in Excel tramite dati JSON
Ecco uno snippet di codice di esempio per dimostrare come importare dati da un DataFrame panda in un file Excel utilizzando Aspose.Cells for Python via .NET:
- Crea un campione di dati DataFrame di Panda.
- Utilizza la libreria panda per convertire i dati DataFrame in dati JSON.
- Importa i dati JSON utilizzando Aspose.Cells for Python via .NET.
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import pandas as pd | |
from aspose.cells.utility import JsonUtility, JsonLayoutOptions | |
from aspose.cells import Workbook, Worksheet, Cells | |
# Create a sample pandas DataFrame | |
data = {'Name': ['Alice', 'Bob', 'Charlie'], | |
'Age': [25, 30, 35], | |
'City': ['New York', 'San Francisco', 'Los Angeles']} | |
df = pd.DataFrame(data) | |
# Convert pandas DataFrame to JSON | |
json_string = df.to_json(orient='records') | |
workbook = Workbook() | |
# Get the first worksheet | |
worksheet = workbook.worksheets[0] | |
# Get the cells | |
cells = worksheet.cells | |
options = JsonLayoutOptions() | |
unit = JsonUtility() | |
# Processes as table. | |
options.array_as_table = True | |
unit.import_data(json_string, cells, 0, 0, options) | |
workbook.save("out.xlsx") |
Converti direttamente Pandas DataFrame in Excel
Ecco uno snippet di codice di esempio per dimostrare come importare dati da un DataFrame panda in un file Excel utilizzando Aspose.Cells for Python via .NET:
- Crea un campione di dati DataFrame di Panda.
- Attraversa DataFrame e importa i dati utilizzando Aspose.Cells for Python via .NET.
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import pandas as pd | |
import aspose.cells | |
from aspose.cells import Workbook, CellsHelper, License | |
workbook = Workbook() | |
# Get the first worksheet | |
worksheet = workbook.worksheets[0] | |
# Get the cells | |
cells = worksheet.cells | |
# create a sample DataFrame | |
data = {'name': ['Alice', 'Bob', 'Charlie', 'David'], | |
'age': [25, 32, 18, 47], | |
'city': ['New York', 'Paris', 'London', 'Berlin']} | |
df = pd.DataFrame(data) | |
rowindex = 0 | |
colindex = 0 | |
for column in df: | |
cell = cells.get(rowindex, colindex) | |
cell.put_value(df[column].name) | |
colindex += 1 | |
for index, row in df.iterrows(): | |
rowindex += 1 | |
colindex = 0 | |
cell = cells.get(rowindex, colindex) | |
cell.put_value(row["name"]) | |
colindex += 1 | |
cell = cells.get(rowindex, colindex) | |
cell.put_value(row["age"]) | |
colindex += 1 | |
cell = cells.get(rowindex, colindex) | |
cell.put_value(row["city"]) | |
colindex += 1 | |
workbook.save("out.xlsx") |