I am following the Udacity data Science into course and my solution was exactly the one they provided
import pandas
import pandasql
def select_first_50(filename):
# Read in our aadhaar_data csv to a pandas dataframe. Afterwards, we rename the columns
# by replacing spaces with underscores and setting all characters to lowercase, so the
# column names more closely resemble columns names one might find in a table.
aadhaar_data = pandas.read_csv(filename)
aadhaar_data.rename(columns = lambda x: x.replace(' ', '_').lower(), inplace=True)
# Select out the first 50 values for "registrar" and "enrolment_agency"
# in the aadhaar_data table using SQL syntax.
#
# Note that "enrolment_agency" is spelled with one l. Also, the order
# of the select does matter. Make sure you select registrar then enrolment agency
# in your query.
#
# You can download a copy of the aadhaar data that we are passing
# into this exercise below:
# https://s3.amazonaws.com/content.udacity-data.com/courses/ud359/aadhaar_data.csv
q = """
SELECT registrar, enrolment_agency FROM aadhar_data LIMIT 50;
"""
#Execute your SQL command against the pandas frame
aadhaar_solution = pandasql.sqldf(q.lower(), locals())
return aadhaar_solution
print select_first_50("/home/trina/Documents/Udacity_datascience/aadhaar_data.csv")
however it returns me this error:
File "pandas_sql.py", line 29, in <module>
print select_first_50("/home/trina/Documents/Udacity_datascience/aadhaar_data.csv")
File "pandas_sql.py", line 26, in select_first_50
aadhaar_solution = pandasql.sqldf(q.lower(), locals())
File "/home/trina/anaconda2/lib/python2.7/site-packages/pandasql/sqldf.py", line 156, in sqldf
return PandaSQL(db_uri)(query, env)
File "/home/trina/anaconda2/lib/python2.7/site-packages/pandasql/sqldf.py", line 63, in __call__
raise PandaSQLException(ex)
pandasql.sqldf.PandaSQLException: (sqlite3.OperationalError) no such table: aadhar_data [SQL: '\n\tselect registrar, enrolment_agency from aadhar_data limit 50;\n\t']
Can you please help me figure out what's going wrong in my code? thanks in advance!