pandas read in txt file without headers
<p>I am new to pandas and I thought it would be a good idea to give it a spin but as so often the first time appears to be not so easy.</p>

<p>I basically tried the following:
<a href="https://stackoverflow.com/questions/29287224/pandas-read-in-table-without-headers">Pandas read in table without headers</a></p>

<p>And I get the following error (unfortunately <em>Usecols do not match names</em> does not ring a bell since I set header to None):</p>

<blockquote>
  <p>ValueError: Usecols do not match names.</p>
</blockquote>

<p>here is my code:</p>

<pre><code>import numpy as np

DATA_FOLDER = 'season_1/training_data/'

#data = np.loadtxt(DATA_FOLDER + 'order_data/order_data_sample', 
#                  dtype={'names': ('order_id', 'driver_id', 'passenger_id', 'start_district_hash',
#                                   'dest_distric_hash', 'price', 'time'),
#...                      'formats': ('S32', 'S32', 'S32', 'S32', 'S32', 'f6', 'f4')})

import pandas as pd
df = pd.read_csv(DATA_FOLDER + 'order_data/order_data_sample', parse_dates=[6], header=None, usecols=[3, 4, 6])
df
</code></pre>

<p>and my data:</p>

<pre><code>97ebd0c6680f7c0535dbfdead6e51b4b  dd65fa250fca2833a3a8c16d2cf0457c  ed180d7daf639d936f1aeae4f7fb482f  4725c39a5e5f4c188d382da3910b3f3f  3e12208dd0be281c92a6ab57d9a6fb32  24  2016-01-01 13:37:23
92c3ac9251cc9b5aab90b114a1e363be  c077e0297639edcb1df6189e8cda2c3d  191a180f0a262aff3267775c4fac8972  82cc4851f9e4faa4e54309f8bb73fd7c  b05379ac3f9b7d99370d443cfd5dcc28  2 2016-01-01 09:47:54
abeefc3e2aec952468e2fd42a1649640  86dbc1b68de435957c61b5a523854b69  7029e813bb3de8cc73a8615e2785070c  fff4e8465d1e12621bc361276b6217cf  fff4e8465d1e12621bc361276b6217cf  9 2016-01-01 18:24:02
cb31d0be64cda3cc66b46617bf49a05c  4fadfa6eeaa694742de036dddf02b0c4  21dc133ac68e4c07803d1c2f48988a83  4b7f6f4e2bf237b6cc58f57142bea5c0  4b7f6f4e2bf237b6cc58f57142bea5c0  11  2016-01-01 22:13:27
139d492189ae5a933122c098f63252b3  NULL  26963cc76da2d8450d8f23fc357db987  fc34648599753c9e74ab238e9a4a07ad  87285a66236346350541b8815c5fae94  4 2016-01-01 17:00:06
</code></pre>

<p>I hope I have used the right tags for this...</p>