pandas | practice using the new features

by guoanjie C++ Version: Current License: MIT

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kandi X-RAY | pandas Summary

pandas is a C++ library typically used in Data Science applications. pandas has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

This project is for me to practice using the new features of modern C++, by re-implementing a few functionalities of pandas - Python Data Analysis Library. The goal of using as many C++14/17/20 features as possible is inspired by Jonathan Boccara's blog post The Expressive C++17 Coding Challenge.

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Support

pandas has a low active ecosystem.

It has 5 star(s) with 0 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

pandas has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pandas is current.

Quality

pandas has no bugs reported.

Security

pandas has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

pandas is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

pandas releases are not available. You will need to build from source code and install.

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Community Discussions

Trending Discussions on pandas

Pandas: List of maximum values of difference from previous rows in new column

repeat values of a column based on a condition

Identify distinct mappings of two overlapping columns in Pandas

drop a level two column from multi index dataframe

Create new columns based on rank order in Pandas

Filter dictionary whose values are arrays

Check Graph Reciprocity using Pandas

Parsing XML using Python and create an excel report - Elementree/lxml

Deleting columns with specific conditions

How to look up data in a separate dataframe (df2) based on date in df1 falling between date range values across two columns in df2

QUESTION

Pandas: List of maximum values of difference from previous rows in new column

Asked 2021-Jun-16 at 03:33

I want to add a new column 'BEST' to this dataframe, which contains a list of the names of the columns which meet these criteria:

Subtract from the current value in each column the value in the row that is 2 rows back
The column that has the highest result of this subtraction will be listed in 'BEST'
If more more than one column shares the same highest result, they all get listed
If all columns have the same result, they all get listed

Input:

...

ANSWER

Answered 2021-Jun-16 at 03:33

First use shift and subtract to get the diff, then replace the maximum values with the column name and drop the others.

Source https://stackoverflow.com/questions/67995888

QUESTION

repeat values of a column based on a condition

Asked 2021-Jun-16 at 00:54

I have a data frame including three columns named 'Altitude', 'Distance', 'Slope'. The column of 'Slope' is calculated using the two first columns 'Altitude', 'Distance'. @ the first step the purpose was to calculate 'Slope' using a condition explained below: A condition function was deployed to start from the top column of the "Distance" variable and add up (sum) values until the summation of them is greater or equal to 10 (>=10). If this condition corrects then calculate the "Slope" using the given formula: Slope=Average(Altitude)/(sum(Distance)). The summation of the 'Distance' was counting from the first value of that to the index that the 'Distance' has stopped there). The following code is for the above explanation (By Tim Roberts):

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ANSWER

Answered 2021-May-19 at 13:38

Use this code after you calculate s to get slope column with desired values:

Source https://stackoverflow.com/questions/67602985

QUESTION

Identify distinct mappings of two overlapping columns in Pandas

Asked 2021-Jun-15 at 20:56

Suppose I have a Pandas dataframe with two identifier columns like this:

...

ANSWER

Answered 2021-Jun-15 at 20:56

Sounds like a network issue, try with networkx

Source https://stackoverflow.com/questions/67993365

QUESTION

drop a level two column from multi index dataframe

Asked 2021-Jun-15 at 20:39

Consider this dataframe:

...

ANSWER

Answered 2021-Jun-15 at 20:30

Try:

Source https://stackoverflow.com/questions/67993054

QUESTION

Create new columns based on rank order in Pandas

Asked 2021-Jun-15 at 19:02

I have a data frame like this,

...

ANSWER

Answered 2021-Jun-11 at 05:56

df = df.set_index(["ID", "Rank"])
df = df.unstack("Rank")
df.columns = df.columns.map(lambda col: "_".join(map(str, col)))

Source https://stackoverflow.com/questions/67931685

QUESTION

Filter dictionary whose values are arrays

Asked 2021-Jun-15 at 18:35

I have data which looks like this:

...

ANSWER

Answered 2021-Jun-15 at 18:35

import numpy as np

features_dict = {
    'feat1': np.array([[0,1],[2,3],[4,5]]), 
    'feat2': np.array([[6,7],[8,9],[10,11]]),
    'feat3': np.array([1, 0, 0]),
    'feat4': np.array([[1],[2],[1]])
}

ind = features_dict['feat3'] == 0
features_dict = {k: v[ind] for k,v in features_dict.items()}

Source https://stackoverflow.com/questions/67991514

QUESTION

Check Graph Reciprocity using Pandas

Asked 2021-Jun-15 at 18:22

I have a Graph loaded in pandas and I want to check if my graph has nodes with reciprocity. My dataset looks like this:

id from to 0 s01 s03 1 s02 s01 2 s03 s01

The desired output of my code is the reciprocal nodes: (s01, s03)

I found a solution transforming my dataframe into tuples and comparing each combination of my nodes, but I'm sure this solution is far from ideal. Following is my code:

...

ANSWER

Answered 2021-Jun-15 at 18:22

You can merge the DataFrame with itself after swapping the from and to columns in the right DataFrame. Then sort the merged result and drop duplicates to get the unique pairs of reciprocal nodes.

Source https://stackoverflow.com/questions/67991543

QUESTION

Parsing XML using Python and create an excel report - Elementree/lxml

Asked 2021-Jun-15 at 17:46

I am trying to parse many XML test results files and get the necessary data like testcase name, test result, failure message etc to an excel format. I decided to go with Python.

My XML file is a huge file and the format is as follows. The cases which failed has a message, & and the passed ones only has . My requirement is to create an excel with testcasename, test status(pass/fail), test failure message.

...

ANSWER

Answered 2021-Jun-15 at 17:46

Since your XML is relatively flat, consider a list/dictionary comprehension to retrieve all child elements and attrib dictionary. From there, call pd.concat once outside the loop. Below runs a dictionary merge (Python 3.5+).

Source https://stackoverflow.com/questions/67977767

QUESTION

Deleting columns with specific conditions

Asked 2021-Jun-15 at 16:53

I have a dataframe output from the python script which gives following output

Datetime High Low Time 546 2021-06-15 14:30:00 15891.049805 15868.049805 14:30:00 547 2021-06-15 14:45:00 15883.000000 15869.900391 14:45:00 548 2021-06-15 15:00:00 15881.500000 15866.500000 15:00:00 549 2021-06-15 15:15:00 15877.750000 15854.549805 15:15:00 550 2021-06-15 15:30:00 15869.250000 15869.250000 15:30:00

i Want to remove all rows where time is equal to 15:30:00. tried different things but unable to do. Help please.

...

ANSWER

Answered 2021-Jun-15 at 15:55

The way I did was the following,

First we get the the time we want to remove from the dataset, that is 15:30:00 in this case.

Since the Datetime column is in the datetime format, we cannot compare the time as strings. So we convert the given time in the datetime.time() format.

rm_time = dt.time(15,30)

With this, we can go about using the DataFrame.drop()

df.drop(df[df.Datetime.dt.time == rm_time].index)

Source https://stackoverflow.com/questions/67989337

QUESTION

How to look up data in a separate dataframe (df2) based on date in df1 falling between date range values across two columns in df2

Asked 2021-Jun-15 at 16:38

Situation: I have two dataframes df1 and df2, where df1 has a datetime index based on days, and df2 has two date columns 'wk start' and 'wk end' that are weekly ranges as well as one data column 'statistic' that stores data corresponding to the week range.

What I would like to do: Add to df1 a column for 'statistic' whereby I lookup each date (on a daily basis, i.e. each row) and try to find the corresponding 'statistic' depending on the week that this date falls into.

I believe the answer would require merging df2 into df1 but I'm lost as to how to proceed after that.

Appreciate any help you might provide! Thanks!

df1: (note: I skipped the rows between 2019-06-12 and 2019-06-16 to keep the example short.)

age date 2019-06-10 20 2019-06-11 21 2019-06-17 19 2019-06-18 18

df2:

wk start wk end statistic 2019-06-10 2019-06-14 102 2019-06-17 2019-06-21 100 2019-06-24 2019-06-28 547 2019-07-02 2019-07-25 268

Desired output:

age statistic date :--- :-------- 2019-06-10 20 102 2019-06-11 21 102 2019-06-17 19 100 2019-06-18 18 100

code for the dataframes d1 and d2

...

ANSWER

Answered 2021-Jun-15 at 09:37

You could loop through the dataframe and subset the second dataframe as you go.

Source https://stackoverflow.com/questions/67983367

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