Code Sample, a copy-pastable example if possible
#!/usr/bin/python
import MySQLdb
import pandas as pd
import pprint as pp
import os
import sys
import HTMLParser
parser = HTMLParser.HTMLParser()
def get_script_path():
return os.path.dirname(os.path.realpath(sys.argv[0]))
script_path = get_script_path()
db = MySQLdb.connect("","","","" )
df = pd.read_sql("SELECT * from test limit 1000",db)
df.to_json(script_path+'/query_resutls.json')
Problem description
I got a plain 'Segmentation fault: 11' when running this code on the Terminal.app I believe the problem was that one of the columns had currency names encoded in HTML. The USD are encoded as "Dólares" from the spanish "Dólares".
pandas (0.20.3) Python 2.7.13 MacOS High Sierra 10.13.2
Output of pd.show_versions()
[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.13.final.0
python-bits: 64
OS: Darwin
OS-release: 17.3.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.20.3
pytest: None
pip: 9.0.1
setuptools: 36.6.0
Cython: None
numpy: 1.13.3
scipy: None
xarray: None
IPython: 5.4.1
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.6.0
html5lib: 0.9999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
Comment From: chris-b1
Using the mysql library directly is as far as I understand deprecated in favor of using sqlalchemy - what happens if you use it?
https://pandas.pydata.org/pandas-docs/stable/io.html#sql-queries
Comment From: ghost
I worked around this.
