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0 votes
in Data Science by (17.6k points)

I have a csv file from this webpage. I want to read some of the columns in the downloaded file (the csv version can be downloaded in the upper right corner).

Let's say I want 2 columns:

1.59 which in the header is star_name

2.60 which in the header is ra.

However, for some reason the authors of the webpage sometimes decide to move the columns around.

In the end I want something like this, keeping in mind that values can be missing.

data = #read data in a clever way

names = data['star_name']

ras = data['ra']

This will prevent my program to malfunction when the columns are changed again in the future, if they keep the name correct.

Until now I have tried various ways using the csv module and resently the pandas module. Both without any luck.

EDIT (added two lines + the header of my datafile. Sorry, but it's extremely long.)

# name, mass, mass_error_min, mass_error_max, radius, radius_error_min, radius_error_max, orbital_period, orbital_period_err_min, orbital_period_err_max, semi_major_axis, semi_major_axis_error_min, semi_major_axis_error_max, eccentricity, eccentricity_error_min, eccentricity_error_max, angular_distance, inclination, inclination_error_min, inclination_error_max, tzero_tr, tzero_tr_error_min, tzero_tr_error_max, tzero_tr_sec, tzero_tr_sec_error_min, tzero_tr_sec_error_max, lambda_angle, lambda_angle_error_min, lambda_angle_error_max, impact_parameter, impact_parameter_error_min, impact_parameter_error_max, tzero_vr, tzero_vr_error_min, tzero_vr_error_max, K, K_error_min, K_error_max, temp_calculated, temp_measured, hot_point_lon, albedo, albedo_error_min, albedo_error_max, log_g, publication_status, discovered, updated, omega, omega_error_min, omega_error_max, tperi, tperi_error_min, tperi_error_max, detection_type, mass_detection_type, radius_detection_type, alternate_names, molecules, star_name, ra, dec, mag_v, mag_i, mag_j, mag_h, mag_k, star_distance, star_metallicity, star_mass, star_radius, star_sp_type, star_age, star_teff, star_detected_disc, star_magnetic_field

11 Com b,19.4,1.5,1.5,,,,326.03,0.32,0.32,1.29,0.05,0.05,0.231,0.005,0.005,0.011664,,,,,,,,,,,,,,,,,,,,,,,,,,,,,1,2008,2011-12-23,94.8,1.5,1.5,2452899.6,1.6,1.6,Radial Velocity,,,,,11 Com,185.1791667,17.7927778,4.74,,,,,110.6,-0.35,2.7,19.0,G8 III,,4742.0,,

11 UMi b,10.5,2.47,2.47,,,,516.22,3.25,3.25,1.54,0.07,0.07,0.08,0.03,0.03,0.012887,,,,,,,,,,,

1 Answer

0 votes
by (41.4k points)

An easy way to do this is using the pandas library like this.

import pandas as pd

fields = ['star_name', 'ra']

df = pd.read_csv('data.csv', skipinitialspace=True, usecols=fields)

# See the keys

print df.keys()

# See content in 'star_name'

print df.star_name

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