extracting-financial-statements-from-sec-filings.ipynb

extracting-financial-statements-from-sec-filings.ipynb

@janlukasschroeder Getting errors trying to output of
statement_1 = add_fourth_quarter_results(statement)

While trying to extract data from ticker:MU (Micron Technology).

 41                     for row_key, row_value in statement[column].iteritems():
---> 42                         value = num(statement[column][row_key]) - num(statement[column_1][row_key])
   44                         if isinstance(value, float):
   45                             value = round(value, 2)

TypeError: cannot convert the series to <class 'int'>

Any fix?

does this also work for the balance sheet and cash flow statement? bumping up against the call requests

Thank you for that. Will try these on my end.

On Wed, May 24, 2023 at 10:43 PM Srujan Taticherla ***@***.***> wrote: ***@***.**** commented on this gist. ------------------------------ Balance sheet I have checked seems to work. (only until the before part where we add the 4th quarter, did not try that yet). But cash flow looks like has an issue because the indices returned by the data frame for each ascension number is not the same. So the procedure "merge_income_statements" will have an error - KeyError: Index. trying to check work arounds for it. trying this instead of existing procedure call for merge. Not sure if the results are OK yet. cash_flow_final_reset = cash_flow_final.reset_index() cash_flow_cleaned_reset = cash_flow_cleaned.reset_index() Perform the merge operation on the reset indices merged_df = cash_flow_final_reset.merge(cash_flow_cleaned_reset, how='outer', on='index', suffixes=('_left', '')) Set the index back to the original column or choose a new index column merged_df.set_index('index', inplace=True) merged_df=clean_income_statement(merged_df) display(HTML(merged_df.to_html())) — Reply to this email directly, view it on GitHub <https://gist.github.com/janlukasschroeder/3da274150fd00c1c1776c7e541a9b61b#gistcomment-4578900> or unsubscribe <https://github.com/notifications/unsubscribe-auth/AKOV6OPSHWGF6L4GQTXBJNDXH3BOTBFKMF2HI4TJMJ2XIZLTSKBKK5TBNR2WLJDHNFZXJJDOMFWWLK3UNBZGKYLEL52HS4DFQKSXMYLMOVS2I5DSOVS2I3TBNVS3W5DIOJSWCZC7OBQXE5DJMNUXAYLOORPWCY3UNF3GS5DZVRZXKYTKMVRXIX3UPFYGLK2HNFZXIQ3PNVWWK3TUUZ2G64DJMNZZDAVEOR4XAZNEM5UXG5FFOZQWY5LFVEYTCNBVGYYDAMJRU52HE2LHM5SXFJTDOJSWC5DF> . You are receiving this email because you commented on the thread. Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub> .

-- Sean Gearin 617-455-2891 ***@***.***

Do you have any API's to extract the stock prices (current , history)..?

https://pypi.org/project/yfinance/

On Thu, May 25, 2023 at 7:44 PM Srujan Taticherla ***@***.***> wrote: ***@***.**** commented on this gist. ------------------------------ Do you have any API's to extract the stock prices (current , history)..? — Reply to this email directly, view it on GitHub <https://gist.github.com/janlukasschroeder/3da274150fd00c1c1776c7e541a9b61b#gistcomment-4579944> or unsubscribe <https://github.com/notifications/unsubscribe-auth/AKOV6OLZTUKUBXMTY53PAETXH7VE5BFKMF2HI4TJMJ2XIZLTSKBKK5TBNR2WLJDHNFZXJJDOMFWWLK3UNBZGKYLEL52HS4DFQKSXMYLMOVS2I5DSOVS2I3TBNVS3W5DIOJSWCZC7OBQXE5DJMNUXAYLOORPWCY3UNF3GS5DZVRZXKYTKMVRXIX3UPFYGLK2HNFZXIQ3PNVWWK3TUUZ2G64DJMNZZDAVEOR4XAZNEM5UXG5FFOZQWY5LFVEYTCNBVGYYDAMJRU52HE2LHM5SXFJTDOJSWC5DF> . You are receiving this email because you commented on the thread. Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub> .

-- Sean Gearin 617-455-2891 ***@***.***

How do you think about dealing with REVISIONS point-in-time, similar to the vintage problem that ALFRED tries to solve for economic data? We know the PIT when the data was released, given the accceptanceDateTime via the accession_number