The program snippet below crashes the python interpreter. I have run the snippet with:
all with the same result (sometimes I have run it twice and it crashes the next time, don't know why).
import pandas as pd
categories = ['Afghanistan', 'Albania', 'Algeria', 'Andorra', 'Angola', 'Antigua & Deps', 'Argentina', 'Armenia', 'Australia', 'Austria', 'Azerbaijan', 'Bahamas', 'Bahrain', 'Bangladesh', 'Barbados', 'Belarus', 'Belgium', 'Benin', 'Bhutan', 'Bolivia', 'Bosnia Herzegovina', 'Botswana', 'Brazil', 'Brunei', 'Bulgaria', 'Burkina', 'Cambodia', 'Cameroon', 'Canada', 'Chile', 'China', 'Colombia', 'Congo {Democratic Rep}', 'Costa Rica', 'Croatia', 'Cuba', 'Cyprus', 'Czech Republic', 'Denmark', 'Djibouti', 'Dominican Republic', 'Ecuador', 'Egypt', 'El Salvador', 'Estonia', 'Ethiopia', 'Finland', 'France', 'Gabon', 'Georgia', 'Germany', 'Ghana', 'Greece', 'Guatemala', 'Haiti', 'Honduras', 'Hungary', 'Iceland', 'India', 'Indonesia', 'Iran', 'Iraq', 'Ireland {Republic}', 'Israel', 'Italy', 'Jamaica', 'Japan', 'Jordan', 'Kazakhstan', 'Kenya', 'Korea North', 'Korea South', 'Kosovo', 'Kuwait', 'Kyrgyzstan', 'Laos', 'Latvia', 'Lebanon', 'Liechtenstein', 'Lithuania', 'Luxembourg', 'Macedonia', 'Madagascar', 'Malaysia', 'Maldives', 'Malta', 'Mauritania', 'Mauritius', 'Mexico', 'Moldova', 'Mongolia', 'Montenegro', 'Morocco', 'Mozambique', 'Myanmar, {Burma}', 'Namibia', 'Nepal', 'Netherlands', 'New Zealand', 'Nicaragua', 'Nigeria', 'Norway', 'Oman', 'Other', 'Pakistan', 'Panama', 'Paraguay', 'Peru', 'Philippines', 'Poland', 'Portugal', 'Qatar', 'Romania', 'Russian Federation', 'Rwanda', 'San Marino', 'Saudi Arabia', 'Senegal', 'Serbia', 'Sierra Leone', 'Singapore', 'Slovakia', 'Slovenia', 'Solomon Islands', 'Somalia', 'South Africa', 'South Sudan', 'Spain', 'Sri Lanka', 'Sudan', 'Swaziland', 'Sweden', 'Switzerland', 'Syria', 'Taiwan', 'Tajikistan', 'Tanzania', 'Thailand', 'Togo', 'Trinidad & Tobago', 'Tunisia', 'Turkey', 'Turkmenistan', 'Uganda', 'Ukraine', 'United Arab Emirates', 'United Kingdom', 'United States', 'Uruguay', 'Uzbekistan', 'Vanuatu', 'Vatican City', 'Venezuela', 'Vietnam', 'Zambia', 'Zimbabwe', "Didn't answer"]
series0_values = [9, 1, 8, 18, 8, 85, 49, 3, 1, 2, 14, 1, 7, 40, 2, 5, 64, 1, 15, 5, 1, 116, 7, 43, 8, 6, 13, 2, 2, 32, 35, 2, 1, 23, 1, 5, 1, 43, 112, 1, 9, 319, 1, 25, 3, 2, 30, 4, 455, 23, 60, 1, 37, 37, 106, 1, 13, 6, 5, 5, 1, 32, 1, 10, 8, 14, 5, 1, 11, 1, 6, 1, 39, 4, 1, 4, 2, 7, 124, 30, 1, 4, 28, 1, 31, 2, 20, 130, 39, 29, 97, 7, 17, 1, 17, 11, 15, 23, 1, 146, 11, 1, 75, 55, 4, 9, 10, 1, 1, 4, 54, 1, 3, 34, 3, 299, 587, 7, 1, 10, 17, 2, 65]
series0_index = ['Afghanistan', 'Albania', 'Algeria', 'Argentina', 'Armenia', 'Australia', 'Austria', 'Azerbaijan', 'Bahamas', 'Bahrain', 'Bangladesh', 'Barbados', 'Belarus', 'Belgium', 'Bolivia', 'Bosnia Herzegovina', 'Brazil', 'Brunei', 'Bulgaria', 'Cambodia', 'Cameroon', 'Canada', 'Chile', 'China', 'Colombia', 'Costa Rica', 'Croatia', 'Cuba', 'Cyprus', 'Czech Republic', 'Denmark', 'Dominican Republic', 'Ecuador', 'Egypt', 'El Salvador', 'Estonia', 'Ethiopia', 'Finland', 'France', 'Gabon', 'Georgia', 'Germany', 'Ghana', 'Greece', 'Guatemala', 'Honduras', 'Hungary', 'Iceland', 'India', 'Indonesia', 'Iran', 'Iraq', 'Ireland {Republic}', 'Israel', 'Italy', 'Jamaica', 'Japan', 'Jordan', 'Kazakhstan', 'Kenya', 'Korea North', 'Korea South', 'Kyrgyzstan', 'Latvia', 'Lebanon', 'Lithuania', 'Macedonia', 'Madagascar', 'Malaysia', 'Maldives', 'Malta', 'Mauritius', 'Mexico', 'Moldova', 'Mongolia', 'Morocco', 'Myanmar, {Burma}', 'Nepal', 'Netherlands', 'New Zealand', 'Nicaragua', 'Nigeria', 'Norway', 'Oman', 'Pakistan', 'Peru', 'Philippines', 'Poland', 'Portugal', 'Romania', 'Russian Federation', 'Saudi Arabia', 'Serbia', 'Sierra Leone', 'Singapore', 'Slovakia', 'Slovenia', 'South Africa', 'South Sudan', 'Spain', 'Sri Lanka', 'Sudan', 'Sweden', 'Switzerland', 'Syria', 'Taiwan', 'Thailand', 'Togo', 'Trinidad & Tobago', 'Tunisia', 'Turkey', 'Turkmenistan', 'Uganda', 'Ukraine', 'United Arab Emirates', 'United Kingdom', 'United States', 'Uruguay', 'Uzbekistan', 'Venezuela', 'Vietnam', 'Zimbabwe', "Didn't answer"]
i0 = pd.CategoricalIndex(series0_index, ordered=True, categories=categories)
s0 = pd.Series(series0_values, index=i0)
series1_values = [4, 18, 16, 65, 33, 2, 8, 1, 12, 35, 3, 3, 46, 6, 1, 89, 4, 17, 8, 6, 3, 2, 1, 22, 30, 3, 13, 1, 9, 1, 35, 109, 7, 197, 1, 14, 2, 17, 233, 9, 28, 16, 36, 56, 5, 1, 3, 4, 6, 14, 3, 8, 3, 3, 3, 14, 2, 1, 3, 1, 3, 5, 86, 11, 1, 3, 20, 12, 2, 1, 1, 7, 93, 20, 18, 61, 3, 14, 1, 5, 9, 5, 1, 19, 80, 4, 1, 75, 29, 2, 6, 11, 1, 2, 34, 45, 6, 281, 580, 6, 1, 5, 10, 1, 36]
series1_index = ['Afghanistan', 'Argentina', 'Armenia', 'Australia', 'Austria', 'Bahrain', 'Bangladesh', 'Barbados', 'Belarus', 'Belgium', 'Bolivia', 'Bosnia Herzegovina', 'Brazil', 'Bulgaria', 'Cambodia', 'Canada', 'Chile', 'China', 'Colombia', 'Costa Rica', 'Croatia', 'Cuba', 'Cyprus', 'Czech Republic', 'Denmark', 'Ecuador', 'Egypt', 'El Salvador', 'Estonia', 'Ethiopia', 'Finland', 'France', 'Georgia', 'Germany', 'Ghana', 'Greece', 'Guatemala', 'Hungary', 'India', 'Indonesia', 'Iran', 'Ireland {Republic}', 'Israel', 'Italy', 'Japan', 'Jordan', 'Kazakhstan', 'Kenya', 'Korea South', 'Latvia', 'Lebanon', 'Lithuania', 'Macedonia', 'Malaysia', 'Malta', 'Mexico', 'Moldova', 'Mongolia', 'Morocco', 'Mozambique', 'Myanmar, {Burma}', 'Nepal', 'Netherlands', 'New Zealand', 'Nicaragua', 'Nigeria', 'Norway', 'Pakistan', 'Panama', 'Paraguay', 'Peru', 'Philippines', 'Poland', 'Portugal', 'Romania', 'Russian Federation', 'Saudi Arabia', 'Serbia', 'Sierra Leone', 'Singapore', 'Slovakia', 'Slovenia', 'Solomon Islands', 'South Africa', 'Spain', 'Sri Lanka', 'Swaziland', 'Sweden', 'Switzerland', 'Syria', 'Taiwan', 'Thailand', 'Trinidad & Tobago', 'Tunisia', 'Turkey', 'Ukraine', 'United Arab Emirates', 'United Kingdom', 'United States', 'Uruguay', 'Uzbekistan', 'Venezuela', 'Vietnam', 'Zimbabwe', "Didn't answer"]
i1 = pd.CategoricalIndex(series1_index, ordered=True, categories=categories)
s1 = pd.Series(series1_values, index=i1)
series2_values = [7, 1, 6, 2, 49, 26, 1, 1, 1, 25, 3, 18, 9, 63, 1, 2, 5, 1, 3, 2, 17, 23, 4, 3, 15, 55, 2, 2, 172, 7, 1, 17, 1, 41, 4, 6, 13, 8, 61, 2, 4, 1, 4, 2, 3, 1, 3, 2, 9, 1, 1, 63, 13, 16, 3, 1, 4, 59, 11, 3, 22, 2, 5, 1, 2, 2, 7, 8, 50, 2, 39, 35, 2, 1, 14, 6, 1, 191, 312, 5, 1, 1, 1, 32]
series2_index = ['Afghanistan', 'Angola', 'Argentina', 'Armenia', 'Australia', 'Austria', 'Azerbaijan', 'Bangladesh', 'Belarus', 'Belgium', 'Bosnia Herzegovina', 'Brazil', 'Bulgaria', 'Canada', 'Chile', 'China', 'Colombia', 'Costa Rica', 'Croatia', 'Cyprus', 'Czech Republic', 'Denmark', 'Egypt', 'Estonia', 'Finland', 'France', 'Gabon', 'Georgia', 'Germany', 'Greece', 'Honduras', 'Hungary', 'Iceland', 'India', 'Indonesia', 'Iran', 'Ireland {Republic}', 'Israel', 'Italy', 'Kazakhstan', 'Korea South', 'Laos', 'Latvia', 'Lebanon', 'Lithuania', 'Luxembourg', 'Malaysia', 'Malta', 'Mexico', 'Mongolia', 'Nepal', 'Netherlands', 'New Zealand', 'Norway', 'Pakistan', 'Paraguay', 'Philippines', 'Poland', 'Portugal', 'Romania', 'Russian Federation', 'Saudi Arabia', 'Serbia', 'Sierra Leone', 'Singapore', 'Slovakia', 'Slovenia', 'South Africa', 'Spain', 'Sri Lanka', 'Sweden', 'Switzerland', 'Taiwan', 'Thailand', 'Turkey', 'Ukraine', 'United Arab Emirates', 'United Kingdom', 'United States', 'Uruguay', 'Venezuela', 'Vietnam', 'Zimbabwe', "Didn't answer"]
i2 = pd.CategoricalIndex(series2_index, ordered=True, categories=categories)
s2 = pd.Series(series2_values, index=i2)
print("Before")
x = pd.concat([s0, s1, s2], axis=1) # crash!
print("After")
pd.concat([s0, s1, s2], axis=1) crashes the interpreter for me. If only one or two series are concatenated, no crash occurs
The interpreter just exits with a message in a message box (In danish, but translated to An error caused Python to exit) and the program shuts down. There is no traceback or other information about the cause (that I know how to get at - If I'm instructed to how to get it, I may be able to fetch it).
pd.concat should return a three-column DataFrame. Instead the interpreter crashes.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4