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How to get Dataframe with Table ID in Pandas?


By : Devesh Mishra
Date : October 14 2020, 02:21 PM
I wish this helpful for you I would look at how the URL passes params and probably try to read a dataframe directly from it. I'm unsure if you are trying to develop a function or a script or just exercising.
If you do (notice the 58 at the end of the url)
code :
df = pd.read_html("http://eciresults.nic.in/statewiseS12.htm?st=S1258",attrs = {'id': 
'ctl00_Menu1'})
[                                  0          1   2  \
 0                         Partywise  Partywise NaN   
 1                         Partywise        NaN NaN   
 2  Constituencywise-All  Candidates        NaN NaN   
 3           Constituencywise Trends        NaN NaN   

                                   3                                 4   5  \
 0  Constituencywise-All  Candidates  Constituencywise-All  Candidates NaN   
 1                               NaN                               NaN NaN   
 2                               NaN                               NaN NaN   
 3                               NaN                               NaN NaN   

                          6                        7  
 0  Constituencywise Trends  Constituencywise Trends  
 1                      NaN                      NaN  
 2                      NaN                      NaN  
 3                      NaN                      NaN  ]


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Get HTML table into pandas Dataframe, not list of dataframe objects


By : Janice Juszczec
Date : March 29 2020, 07:55 AM
this will help From http://pandas.pydata.org/pandas-docs/version/0.17.1/io.html#io-read-html, "read_html returns a list of DataFrame objects, even if there is only a single table contained in the HTML content".
So df = df[0].dropna(axis=0, thresh=4) should do what you want.

Make equivalent pandas dataframe for sql query containing: join table on itself with selecting all column of 1st table a


By : desmond
Date : March 29 2020, 07:55 AM
will be helpful for those in need I am working on python pandas. I have one table table_one which has columns name,address,one,two,phone. Now one is foreign_key on two , Select required columns before merge (rename it to avoid conflict)
code :
pd.merge(df, df[['two', 'name']].rename(columns={'name', 'for_name'}), left_on=['one'], right_on=['two'])

google finance pandas read table to pandas dataframe


By : Ketle
Date : March 29 2020, 07:55 AM
I wish this helpful for you You can use read_csv with parameters skiprows and names for new column names:
code :
url = 'https://www.google.com/finance/getprices?q=HINDALCO&i=60&p=15d&f=d,o,h,l,c,v'
df = pd.read_csv(url, skiprows=[0,1,2,3,5,6]).rename(columns={'COLUMNS=DATE':'DATE'})

print (df.head())
          DATE   CLOSE    HIGH     LOW    OPEN  VOLUME
0  a1490154300  194.80  194.80  194.80  194.80    2600
1            1  193.55  194.70  193.00  194.15  339142
2            2  193.80  193.95  193.55  193.60  242687
3            3  194.20  194.40  193.80  193.90  119874
4            4  193.80  194.20  193.80  194.20  121355

Python convert multi-column pandas dataframe to single value table dataframe


By : alvo
Date : March 29 2020, 07:55 AM
it helps some times I am looking to convert the following multi-level column pandas dataframe to single value table. , Like @Wen stated use melt:
code :
df.rename_axis('Index').reset_index().melt('Index', value_name='Score')
         Index Name Paper  Score
0   2018-01-01    m     1     13
1   2018-06-01    m     1     11
2   2018-01-01    m     2     33
3   2018-06-01    m     2     43
4   2018-01-01    m     3     15
5   2018-06-01    m     3     30
6   2018-01-01    r     1     31
7   2018-06-01    r     1     36
8   2018-01-01    r     2     25
9   2018-06-01    r     2     23
10  2018-01-01    r     3     33
11  2018-06-01    r     3     37

Sqlalchemy: add into mysql table new rows from pandas dataframe, if they don't exist already in the table


By : Daniel Alcanja
Date : March 29 2020, 07:55 AM
this will help You could pull the results already in the database into a new dataframe and then compare the two dataframes. After that you would only insert the rows not in the table. Not knowing the format of your table or data I'm just using a generic SELECT statement here.
code :
from sqlalchemy import create_engine
from sqlalchemy import exc
engine = create_engine('mysql://usr:psw@ip/schema')
con = engine.connect()
sql = "SELECT * FROM table_name"
old_results = pd.from_sql(sql, con)
df = pd.merge(old_results, results_final, how='outer', indicator=True)
new_results = df[df['_merge']=='right_only'][results_final.columns]
new_results.to_sql(name='error',con=con,if_exists='append')
con.close()
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