A dataframe in Python can be compared to a table in a database. I also get idea that database functionalities are translated into functions that can be found in dataframes. It is also true that a database table can be quickly read into a dataframe. See:<\/p>\n\n\n\n
con = pyodbc.connect('DSN=AzureSQL;UID=tomvanmaanen;PWD=*******')\ncur = con.cursor()\nsql = 'SELECT * FROM AXYWARE.DEELNEMERS_CSV'\ndf = pd.read_sql(sql, con)<\/pre>\n\n\n\nSo, we have a table in a database (AXYWARE.DEELNEMERS_CSV) that is read in a dataframe in just 4 lines of code.<\/p>\n\n\n\n
More or less the same holds for propagating the dataframe into a table:<\/p>\n\n\n\n
from sqlalchemy import create_engine<\/pre>\n\n\n\nengine = create_engine(\"mssql+pyodbc:\/\/tomvanmaanen:*******!@AzureSQL\")\nff.to_sql('Tax_Exception__c', schema='RAPPORTAGE', con = engine, chunksize=100, method='multi', index=False, if_exists='replace')<\/pre>\n\n\n\nJust 3 lines of code, including importing a library to propagate a dataframe (ff) to a table (Tax_Exception__c).<\/p>\n\n\n\n
To access an element within a dataframe, we may either use the labels or the position. So we may use a label approach:<\/p>\n\n\n\n
df.loc[:,\"FirstName\"] to derive a column or df.loc[3,\"FirstName\"] to access a element<\/pre>\n\n\n\nOr we may use the positions:<\/p>\n\n\n\n
df.iloc[:,3] to derive a column or df.loc[3,4] to access a element<\/pre>\n\n\n\nIn most cases, the label to identify a row is the same number that is used to identify a position. So:<\/p>\n\n\n\n
df.iloc[3] equals df.loc[3]\n<\/pre>\n\n\n\nHowever, the philosophy is different. With iloc we address a position. With loc, we address a label. As the label equals the position, the code is equal.<\/p>\n\n\n\n
It is also possible to use this type of coding to update a certain slice of your data frame:<\/p>\n\n\n\n
df.loc[(df['BRPStreetName__c'] == 'Waterlelie') & (df['BRPCityName__c'] == 'GOUDA'),'LastName'] = 'testName'<\/pre>\n\n\n\nSomehow, the ‘loc’ method seems to refer to the same memory position as the original dataframe. this then means that if a slice of the dataframe is referred to by .loc, we may change the content.<\/p>\n\n\n\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
A dataframe in Python can be compared to a table in a database. I also get idea that database functionalities are translated into functions that can be found in dataframes. It is also true that a database table can be quickly read into a dataframe. See: con = pyodbc.connect(‘DSN=AzureSQL;UID=tomvanmaanen;PWD=*******’) cur = con.cursor() sql = ‘SELECT […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-3409","post","type-post","status-publish","format-standard","hentry","category-allgemein"],"_links":{"self":[{"href":"http:\/\/archief.van-maanen.com\/index.php?rest_route=\/wp\/v2\/posts\/3409","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/archief.van-maanen.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/archief.van-maanen.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/archief.van-maanen.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/archief.van-maanen.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3409"}],"version-history":[{"count":0,"href":"http:\/\/archief.van-maanen.com\/index.php?rest_route=\/wp\/v2\/posts\/3409\/revisions"}],"wp:attachment":[{"href":"http:\/\/archief.van-maanen.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3409"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/archief.van-maanen.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3409"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/archief.van-maanen.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3409"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}