I am an elementary Python programmer and have been using this module called "Pybaseball" to analyze sabermetrics data. When using this module, I came across a problem when trying to retrieve information from the program. The program reads a CSV file from any baseball stats site and outputs it onto a program for ease of use but the problem is that some of the information is not shown and is instead all replaced with a "...". An example of this is shown:
from pybaseball import batting_stats_range
data = batting_stats_range('2017-05-01', '2017-05-08')
print(data.head())
I should be getting:
https://github.com/jldbc/pybaseball#batting-stats-hitting-stats-for-players-within-seasons-or-during-a-specified-time-period
But the information is cutoff from 'TM' all the way to 'CS' and is replaced with a ... on my code. Can someone explain to me why this happens and how I can prevent it?
As the docs states, head() is meant for "quickly testing if your object has the right type of data in it." So, it is expected that some data may not show because it is collapsed.
If you need to analyze the data with more detail you can access specific columns with other methods.
For example, using iloc(). You can read more about it here, but essentially you can "ask" for a slice of those columns and then apply a new slice to get only nrows.
Another example would be loc(), docs here. The main difference being that loc() uses labels (column names) to filter data instead of numerical order of columns. You can filter a subset of specific columns and then get a sample of rows from that.
So, to answer your question "..." is pandas's way of collapsing data in order to get a prettier view of the results.
Related
I get data measurements from instruments. These measurements depend on several parameters, and a pivot table is a good solution to represent the data. Every measurement can be associated to a scope screenshoot to be more explicit. I get all the data in the following csv format :
The number of measurements and parameters can change.
I am trying to write a Python script (for now with Pandas lib) which allows me to create a pivot table in Excel. With Pandas, I can color the data in and out of a defined range. However, I would like also to to create a link on every cell who can send me to the corresponding screenshot. But I am stuck here.
I would like a result like the following (but with the link to the corresponding screenshot) :
Actually, I found out a way to add the link thanks to the =HYPERLINK() Excel function to all the cells with the apply() Pandas function.
However, I cannot apply a conditional formatting thanks to xlsxWriter anymore because the cells don't have a numerical content anymore
I can apply the conditional formatting first and then iterate through the whole sheet to add a link, but it will be a total mess to retrieve the relation between the data and the different parameters measurement
I would like your help to find ideas and efficient ways to do what I would like
xlsxwriter has a function called write_url ,but first while creating new worksheet you must apply write_url and then use openyxl to insert your pandas data frame
1)create worksheet and insert write_url
2)use openyxl to write data into already formatted cells.
So, I am trying to pivot this data (link here) to where all the metrics/numbers are in a column with another column being the ID column. Obviously having a ton of data/metrics in a bunch of columns is much harder to compare and do calculations off of than having it all in one column.
So, I know what tools I need for this; Pandas, Findall, Wide_to_long (or melt) and maybe stack. However, I am having a bit of difficulty putting them all in the right place.
I easily can import the data into the df and view it, but when it comes to using findall with wide_to_long to pivot the data I get pretty confused. I am basing my idea off of this example (about half way down when they use the findall / regex to define new column names). I am looking to create a new column for each category of the metrics (ie. population estimate is one column and then % change is another, they should not be all one column)
Can someone help me set up the syntax correctly for this part? I am not good at the expressions dealing with pattern recognition.
Thank you.
I have csv file in excel that looks like this (sorry cant place pictures in the post yet)
RAW DATA
Here is what i want to do:
1) I want python to read through column B and find the phrase RCOM (highlighted)
2) Once it find that phrase, i want it to show me the date entry and the corresponding amounts which i have made bold and are in the red color.
3) hopefully making it read something like this:
30-08-2018 273585.8
27-09-2018 275701.4
25-10-2018 276780
*If possible putting the entries on seperate lines would be great, but if not thats fine too.
4) I will then store these in a variable of my choice and print it out as needed.
I know the column where the word RCOM is located, and i know the column where the amounts i want are located (B and K respectively)
I am very new to coding, any help will be appreciated. Im just trying to automate the boring stuff :)
Thanks
you can generate a data frame using read_csv function from pandas library. Once you have the data in data frame format, you can reach to data mentioned in your question by filtering the data according your requirements. I know this answer is very generic and does not provide a code suggestion but I believe that all information you need can be found in following page https://pandas.pydata.org/pandas-docs/stable/10min.html
For importing data Getting Data In/Out section will be helpful and for filtering (masking) the data Selection section will help.
I'm using the sample Python Machine Learning "IRIS" dataset (for starting point of a project). These data are POSTed into a Flask web service. Thus, the key difference between what I'm doing and all the examples I can find is that I'm trying to load a Pandas DataFrame from a variable and not from a file or URL which both seem to be easy.
I extract the IRIS data from the Flask's POST request.values. All good. But at that point, I can't figure out how to get the pandas dataframe like the "pd.read_csv(....)" does. So far, it seems the only solution is to parse each row and build up several series I can use with the DataFrame constructor? There must be something I'm missing since reading this data from a URL is a simple one-liner.
I'm assuming reading a variable into a Pandas DataFrame should not be difficult since it seems like an obvious use-case.
I tried wrapping with io.StringIO(csv_data), then following up with read_csv on that variable, but that doesn't work either.
Note: I also tried things like ...
data = pd.DataFrame(csv_data, columns=['....'])
but got nothing but errors (for example, "constructor not called correctly!")
I am hoping for a simple method to call that can infer the columns and names and create the DataFrame for me, from a variable, without me needing to know a lot about Pandas (just to read and load a simple CSV data set, anyway).
I am looking to understand how to use a user-defined variable within a column name. I am using pandas. I have a dataframe with several columns that are in the same format, but the code will be run against the different column names. I don't want to have to put in the different column names each time when only the first part of the name actually changes.
For example,
df['input_same_same']
Where the code will call out different columns where only the first part of the column is different and the rest remains the same.
Is it possible to do something along the lines of:
vari='cats' (and the next time I run I can input dogs, pigs, etc)
for
df['vari_count_litter']
I have tried using %s within the column name but that doesn't work.
I'd appreciate any insight or understanding how this is possible. Thanks!
If I understand right, you could do df[vari+'_count_litter']. However, you may be better off using a MultiIndex that would let you do df[vari, 'count_litter']. It's difficult to say how to set it up without know what your data structure is and how you want to access it.