Anatomy of a Field Analysis Worksheet
xleda is a Python/Excel powered EDA tool that creates workbooks from dataframes or data files that are highly optimized to explore, define, and document data sets.
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Works on Windows or MacOS as a Python package, a CLI, or as a service that lets you create workbooks by right-clicking supported files.
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There are some amazing EDA tools available to data professionals. You shouldn't have to start from scratch to include Microsoft Excel among them.
Docs |
Sample Workbooks |
Basic Usage |
Configuration |
Usage Notes |
Examples |
Quick-Start Guide for Non-Developers
Top view of a Field Analysis worksheet.
xleda Components
Basic Usage
Use wb() to quickly create an xleda workbook from a dataframe, a dictionary of dataframes, or a supported data file.
From a Dataframe
from xleda import wb
import seaborn as sns
# < your dataframe goes here >
df = sns.load_dataset("titanic")
# Creates xleda.xlsm in the current directory
wb(df)
From a Dictionary of Dataframes
from xleda import wb
import seaborn as sns
# < your dataframes go here >
df1 = sns.load_dataset("titanic")
df2 = sns.load_dataset("penguins")
# Creates Titanic.xlsm in the current directory
wb({"Titanic": df1,
"Penguins": df2})
From a File
from xleda import wb
from pathlib import Path
# < your data file goes here >
duckdb_file = "https://github.com/InfoDesigner/xleda/raw/refs/heads/main/examples/data/duckdb.duckdb"
# Creates duckdb.xlsm in the current directory
# Includes data from all tables in the db file
wb(duckdb_file)
From the CLI
# Creates 'userdata.xlsm' in the current directory
xleda wb 'https://github.com/InfoDesigner/xleda/raw/refs/heads/main/examples/data/userdata.parquet'
# Shows the help command
xleda --help
# Shows the wb help command
xleda wb --help
From Right-Clicking | After running xleda install
Windows |
MacOS |
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Compatibility
| Desktop Excel |
Requires the full version of Microsoft Excel (2016+) on either MacOS or Windows to create workbooks
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| Supported Data |
Supports pandas dataframes, CSV, DuckDB, SQLite, Feather, Parquet, Pickle, Excel, RData, JSON, and XML |
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