inplace | In-place file processing in Python

by jwodder Python Version: v0.5.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | inplace Summary

inplace is a Python library. inplace has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However inplace build file is not available. You can install using 'pip install inplace' or download it from GitHub, PyPI.

In-place file processing in Python

Support

Quality

Security

License

Reuse

Support

inplace has a low active ecosystem.

It has 18 star(s) with 1 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 4 have been closed. On average issues are closed in 78 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of inplace is v0.5.0

Quality

inplace has no bugs reported.

Security

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

License

inplace 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

inplace releases are available to install and integrate.

Deployable package is available in PyPI.

inplace has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed inplace and discovered the below as its top functions. This is intended to give you an instant insight into inplace implemented functionality, and help decide if they suit your requirements.

Opens the file .
Close the file .
Rolls back the file .
Copy stats from from_file to to to_file .
Try to unlink the given path .
Deprecated .

Get all kandi verified functions for this library.

inplace Key Features

No Key Features are available at this moment for inplace.

inplace Examples and Code Snippets

No Code Snippets are available at this moment for inplace.

Community Discussions

Trending Discussions on inplace

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

How to remove duplicates from a dataframe based on the column with string values

VBA Macro is ignoring nextBlankRow and duplicates

Pandas: Cannot subtract date-time objects (timedelta, datetime)

Python pandas sort_values() with nested list

extract strings and insert as multiple rows based on original index

unable to mmap 1024 bytes - Cannot allocate memory - even though there is more than enough ram

efficiently add rows if discontinuity : cannot reindex from a duplicate axis

python pandas replace all the float values

How to edit columns in .CSV files using pandas

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

QUESTION

How to remove duplicates from a dataframe based on the column with string values

Asked 2021-Jun-15 at 14:29

I am trying to remove duplicates based on the column item_id from a dataframe df.

df :

...

ANSWER

Answered 2021-Jun-15 at 14:29

You can apply a function to the column that will make the item_id "uniform", then can drop_duplicates()

Source https://stackoverflow.com/questions/67988115

QUESTION

VBA Macro is ignoring nextBlankRow and duplicates

Asked 2021-Jun-15 at 13:16

What I want the Macro to accomplish:

I want the user to be able to fill in data from E2 to E9 on the spreadsheet. When the user presses the "Add Car" button the macro is supposed to be executed. The makro then should take the handwritten data, copy everything from E2:E9 and put it into a table that starts at with C13 and spans over 7 columns, always putting the new set of data in the next free row. It is also supposed to check for duplicates and give an alert while not overwriting the original set of data

So my problem is, that I want the Macro I'm writing to take the information put into certain cells and then copy them into a table underneath.

I'm starting the Macro like this

...

ANSWER

Answered 2021-Jun-15 at 13:16

Please, test the next code:

Source https://stackoverflow.com/questions/67981945

QUESTION

Pandas: Cannot subtract date-time objects (timedelta, datetime)

Asked 2021-Jun-15 at 02:51

Here is the setup:

...

ANSWER

Answered 2021-Jun-15 at 01:46

Since both columns are pandas Timestamp, you can do this:

Source https://stackoverflow.com/questions/67978919

QUESTION

Python pandas sort_values() with nested list

Asked 2021-Jun-14 at 16:19

I want to sort a nested dict in pyhon via pandas.

...

ANSWER

Answered 2021-Jun-13 at 15:16

Try:

Source https://stackoverflow.com/questions/67959535

QUESTION

extract strings and insert as multiple rows based on original index

Asked 2021-Jun-14 at 16:07

I have put example dataset (df), expected output (df2) and my code so far below. I have a df where some rows in column i2 contain a list - in the json format, which need exploding and reinserting back into the df, from the row in which they were extracted. But the need to be inputted into a different column (i1). i need to extract a unique identifier (the 'id_2' value) from the string and insert that into the id_2 column.

in my code so far i am parsing the json-like data with pd.normalize, and then inserting the original string from the column i1 onto the top of the extracted strings (it should be much more clear if you take a look below) and then reinsert them based on the index. But I have to specify the index, which is not good. I would like it to be less dependent on manual input of indices in case it changes in the future with more of these nested cells or somehow the index changes.

Any suggestions are very welcome, thanks so much

example data

...

ANSWER

Answered 2021-May-25 at 17:52

Explode the dataframe on column i2, then retrieve the values associated with key item from the column i2 using the str accessor, then using indexing with loc update the values in column i2 to 1 and concatenate the strings in i1 with the retrieved item values

Source https://stackoverflow.com/questions/67692622

QUESTION

unable to mmap 1024 bytes - Cannot allocate memory - even though there is more than enough ram

Asked 2021-Jun-14 at 11:16

I'm currently working on a seminar paper on nlp, summarization of sourcecode function documentation. I've therefore created my own dataset with ca. 64000 samples (37453 is the size of the training dataset) and I want to fine tune the BART model. I use for this the package simpletransformers which is based on the huggingface package. My dataset is a pandas dataframe. An example of my dataset:

My code:

...

ANSWER

Answered 2021-Jun-08 at 08:27

While I do not know how to deal with this problem directly, I had a somewhat similar issue(and solved). The difference is:

I use fairseq
I can run my code on google colab with 1 GPU
Got RuntimeError: unable to mmap 280 bytes from file : Cannot allocate memory (12) immediately when I tried to run it on multiple GPUs.

From the other people's code, I found that he uses python -m torch.distributed.launch -- ... to run fairseq-train, and I added it to my bash script and the RuntimeError is gone and training is going.

So I guess if you can run with 21000 samples, you may use torch.distributed to make whole data into small batches and distribute them to several workers.

Source https://stackoverflow.com/questions/67876741

QUESTION

efficiently add rows if discontinuity : cannot reindex from a duplicate axis

Asked 2021-Jun-14 at 06:38

I have this data. I need help here because If you see the timestamp there is discontinuity and I want to fill it with previous row.

The whole dataset is at 30 min interval, So If you look at the row 3 and 4 there is discontinuity, as you see there is an increase in one hour and then in next row 2 hours. So I want to fill here the missing rows with previous row values by just changing the current timestamp to timestamp+30.

Input Data:

Timestamp eqmt_id brand_brew_code level volume 28-03-2021 09:00 1 AB 12.99 1 28-03-2021 09:30 2 BB 123.43 2 28-03-2021 10:00 1 AB 13.34 3 28-03-2021 11:00 1 AB 213.34 1 28-03-2021 14:00 1 AB 12. 322 1

Expected Outcome:

Timestamp eqmt_id brand_brew_code level volume 28-03-2021 09:00 1 AB 12.99 1 28-03-2021 09:30 2 BB 123.43 2 28-03-2021 10:00 1 AB 13.34 3 28-03-2021 10:30 1 AB 13.34 3 28-03-2021 11:00 1 AB 213.34 1 28-03-2021 11:30 1 AB 213.34 1 28-03-2021 12:00 1 AB 213.34 1 28-03-2021 12:30 1 AB 213.34 1 28-03-2021 13:00 1 AB 213.34 1 28-03-2021 13:30 1 AB 213.34 1 28-03-2021 14:00 1 AB 12. 322 1

I have tried this code but outcome is also matching, but getting stopped in between. Don't know the issue.

...

ANSWER

Answered 2021-Jun-14 at 06:38

IIUC, you can try:

Convert Timestamp to datetime.
Set Timestamp as index.
Use asfreq('30T') to fill the missing time. ffill the missing value with downcast = 'infer' to retain the dtype.
Use reset_index() to get the same structure.

Source https://stackoverflow.com/questions/67965554

QUESTION

python pandas replace all the float values

Asked 2021-Jun-14 at 05:25

The purpose of this code is to:

create a dummy data set.
Then turn it into a data frame
Calculate the peaks and make it a column in the data frame
Calculate the troughs and make it a column in the data frame
Filling the “nan” values with “hold”
Replace all the float values with the word “buy”

The problem is with last step is that it is never worked, but there is no error, it is just print the dataframe just like before this couple of lines.

Here is the code:

...

ANSWER

Answered 2021-May-22 at 16:01

Use np.where to classify it

Source https://stackoverflow.com/questions/67623298

QUESTION

How to edit columns in .CSV files using pandas

Asked 2021-Jun-13 at 15:06

import urllib.request
import pandas as pd

# Url file Website
url = 'https://......CSV'

# Download file
urllib.request.urlretrieve(
    url, "F:\.....A.CSV")

csvFilePath = "F:\.....A.CSV"

df = pd.read_csv(csvFilePath, sep='\t')

rows=[0,1,2,3]
df2 = df.drop(rows, axis=0, inplace=True)
df.to_csv(
    r'F:\....New_A.CSV')

...

ANSWER

Answered 2021-Jun-13 at 14:40

Replace:

Source https://stackoverflow.com/questions/67959379

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install inplace

You can install using 'pip install inplace' or download it from GitHub, PyPI.
You can use inplace like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: