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Tag: pandas

Fill NA and update columns from another dataframe

I want to conditionally fill the missing and update the value from another dataframe. I want to fill missing and update the data on column values in dataframe smalldf. The condition is, if the value in B column (large df) is in the range of columns Range_FROM and Range_TO in (small df). Always choose the minimum records in (largedf) to

Convert SQL commands to Python

I have the following code in SQL: I’ve been trying to rewrite it in python like so: but I keep getting a generic error message. What am I doing wrong? EDIT: added the error message Answer IIUC, you could try the following: The equivalent of SELECT DISTINCT col is drop_duplicates(col) and the equivalent of SELECT col, count(*) is value_counts(col).

find timestamp difference between 2 columns with sqldf

According to this answer: We can use something like this in mysql to calculate the time diff between two cols: How can I achieve the same thing with pandasql? I tried these: but they throw an error that: Answer From the PandaSQL documentation: pandasql uses SQLite syntax. The link in your post is for MySQL. Here is a reference

merging tables with different structures

I have two tables where I want to find the outer join based on a Ticker variable. In Table I, I have only one Ticker for each entity (fund), but in table II, I may have multiple records (multiple Ticker) for each “FundID”. The goal is to count the unique funds. I want to have table III, which is the