Tabular Io

Tabular Data Reading (CSV / TXT)

Description

Read general text-table data files, station lists, and earthquake catalogs. This skill covers robust CSV/TXT parsing and common patterns for data inspection.

Recommended Functions

load_catalog_file(path)

Use this repository helper when the file contains an earthquake catalog or SAGE pick format. Supports .csv, .json, and .txt catalog formats.

from seismo_stats.catalog_loader import load_catalog_file
catalog = load_catalog_file("/data/seismic/waveform/data.csv")
print(catalog.df.head())

pandas.read_csv(path, sep=None, engine='python')

For general CSV or whitespace-delimited .txt tables, use pandas with automatic delimiter detection:

import pandas as pd
path = "/data/seismic/waveform/data.csv"
try:
    df = pd.read_csv(path, sep=None, engine='python')
except Exception:
    df = pd.read_csv(path, delim_whitespace=True, header=None)
print(df.columns)
print(df.head())

# If the file schema is unclear, inspect the file and infer coordinates
if 'latitude' not in df.columns and 'longitude' not in df.columns:
    print('Sample rows:')
    print(df.head(10))
    print('Column names:', df.columns.tolist())
    # Try common coordinate fields
    candidates = [c for c in df.columns if c.lower() in ('lon','lat','lon1','lat1','lon2','lat2','longitude','latitude','x','y')]
    print('Possible coordinate fields:', candidates)

pd.read_table(path, sep='\t')

Use when the file is tab-delimited:

import pandas as pd
path = "/data/seismic/waveform/stations.txt"
df = pd.read_table(path)
print(df.head())

numpy.loadtxt(path, delimiter=',')

For simple numeric tables without headers:

import numpy as np
path = "/data/seismic/waveform/data.txt"
arr = np.loadtxt(path, delimiter=',')
print(arr.shape)
print(arr[:5])

Tips for robust reading

• If the file has no header row, use header=None and assign names=[...].
• If delimiter is unknown, try sep=None, engine='python' or delim_whitespace=True.
• For .txt files, whitespace-delimited data is common.
• If parsing fails, inspect the first few lines with open(path).read().splitlines()[:10].
• Print available column names and sample rows to verify the loaded table.
• When column names are uncertain, search for common alternatives such as lon, lat, lon1, lat1, longitude, latitude, x, y.

Common file patterns

• station_longitude, station_latitude, latitude, longitude
• time, magnitude, depth
• phase, pick_time, confidence
• Data may appear in .csv or .txt files under /data/ or /data/seismic/