DataFrame | C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types and co

by hosseinmoein C++ Version: 2.1.0 License: BSD-3-Clause

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kandi X-RAY | DataFrame Summary

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

This is a C++ analytical library that provides interface and functionality similar to packages/libraries in Python and R. For example, you could compare this to Pandas or R data.frame. You could slice the data in many different ways. You could join, merge, group-by the data. You could run various statistical, summarization, financial, and ML algorithms on the data. You could add your custom algorithms easily. You could multi-column sort, custom pick and delete the data. And more … DataFrame also includes a large collection of analytical algorithms in form of visitors. These are from basic stats such as Mean, Std Deviation, Return, … to more involved analysis such as Affinity Propagation, Polynomial Fit, Fast Fourier transform of arbitrary length … including a good collection of trading indicators. You could also easily add your own algorithms. For basic operations to start you off, see Hello World. For a complete list of features with code samples, see documentation.

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Support

DataFrame has a medium active ecosystem.

It has 1856 star(s) with 264 fork(s). There are 62 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 172 have been closed. On average issues are closed in 12 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of DataFrame is 2.1.0

Quality

DataFrame has 0 bugs and 0 code smells.

Security

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

DataFrame code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

DataFrame is licensed under the BSD-3-Clause License. This license is Permissive.

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

Reuse

DataFrame releases are available to install and integrate.

Installation instructions are not available. Examples and code snippets are available.

It has 17439 lines of code, 0 functions and 182 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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DataFrame Key Features

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DataFrame Examples and Code Snippets

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Community Discussions

Trending Discussions on DataFrame

Good alternative to Pandas .append() method, now that it is being deprecated?

How can I merge two dataframes together with some conditional requirements?

Mapping complex JSON to Pandas Dataframe

How to update pandas DataFrame.drop() for Future Warning - all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only

Merge two pandas DataFrame based on partial match

Dataframe from a character vector where variable name and its data were stored jointly

Use recode to mutate across multiple columns using named list of named vectors

If condition with a dataframe

Create a new column in a Pandas DataFrame from existing column names

Get min and max values of categorical variable in a dataframe

QUESTION

Good alternative to Pandas .append() method, now that it is being deprecated?

Asked 2022-Mar-28 at 02:38

I use the following method a lot to append a single row to a dataframe. One thing I really like about it is that it allows you to append a simple dict object. For example:

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ANSWER

Answered 2022-Jan-24 at 16:57

Create a list with your dictionaries, if they are needed, and then create a new dataframe with df = pd.DataFrame.from_records(your_list). List's "append" method are very efficient and won't be ever deprecated. Dataframes on the other hand, frequently have to be recreated and all data copied over on appends, due to their design - that is why they deprecated the method

Source https://stackoverflow.com/questions/70837397

QUESTION

How can I merge two dataframes together with some conditional requirements?

Asked 2022-Mar-22 at 14:33

I have two dataframes, df1 and df2. I would like to join the two with the following conditions:

merge df1 and df2 on gender and Test
TestDate in df1 need to be within Date1 and Date2 from df2
all.x = TRUE (keep df1 records)

How can I handle the second part?

...

ANSWER

Answered 2022-Mar-21 at 14:44

Does this work for you?

Source https://stackoverflow.com/questions/71559360

QUESTION

Mapping complex JSON to Pandas Dataframe

Asked 2022-Feb-25 at 13:57

Background
I have a complex nested JSON object, which I am trying to unpack into a pandas df in a very specific way.

JSON Object
this is an extract, containing randomized data of the JSON object, which shows examples of the hierarchy (inc. children) for 1x family (i.e. 'Falconer Family'), however there is 100s of them in total and this extract just has 1x family, however the full JSON object has multiple -

...

ANSWER

Answered 2022-Feb-16 at 06:41

I think this gets you pretty close; might just need to adjust the various name columns and drop the extra data (I kept the grouping column).

The main idea is to recursively use pd.json_normalize with pd.concat for all availalable children levels.

EDIT: Put everything into a single function and added section to collapse the name columns like the expected output.

Source https://stackoverflow.com/questions/71104848

QUESTION

How to update pandas DataFrame.drop() for Future Warning - all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only

Asked 2022-Feb-13 at 19:56

The following code:

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ANSWER

Answered 2022-Feb-13 at 19:56

From the documentation, pandas.DataFrame.drop has the following parameters:

Parameters

labels: single label or list-like Index or column labels to drop.

axis: {0 or ‘index’, 1 or ‘columns’}, default 0 Whether to drop labels from the index (0 or ‘index’) or columns (1 or ‘columns’).

index: single label or list-like Alternative to specifying axis (labels, axis=0 is equivalent to index=labels).

columns: single label or list-like Alternative to specifying axis (labels, axis=1 is equivalent to columns=labels).

level: int or level name, optional For MultiIndex, level from which the labels will be removed.

inplace: bool, default False If False, return a copy. Otherwise, do operation inplace and return None.

errors: {‘ignore’, ‘raise’}, default ‘raise’ If ‘ignore’, suppress error and only existing labels are dropped.

Moving forward, only labels (the first parameter) can be positional.

So, for this example, the drop code should be as follows:

Source https://stackoverflow.com/questions/68900763

QUESTION

Merge two pandas DataFrame based on partial match

Asked 2022-Jan-06 at 00:54

Two DataFrames have city names that are not formatted the same way. I'd like to do a Left-outer join and pull geo field for all partial string matches between the field City in both DataFrames.

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ANSWER

Answered 2021-Sep-12 at 20:24

This should do the job. String match with Levenshtein_distance.

pip install thefuzz[speedup]

Source https://stackoverflow.com/questions/69125666

QUESTION

Dataframe from a character vector where variable name and its data were stored jointly

Asked 2021-Dec-27 at 07:53

I've this situation:

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ANSWER

Answered 2021-Dec-26 at 20:48

We may use read.dcf from base R

Source https://stackoverflow.com/questions/70489697

QUESTION

Use recode to mutate across multiple columns using named list of named vectors

Asked 2021-Dec-19 at 17:00

I couldn't find a question similar to the one that I have here. I have a very large named list of named vectors that match column names in a dataframe. I would like to use the list of named vectors to replace values in the dataframe columns that match each list element's name. That is, the name of the vector in the list matches the name of the dataframe column and the key-value pair in each vector element will be used to recode the column.

Reprex below:

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ANSWER

Answered 2021-Dec-13 at 04:44

One work around would be to use your map2_dfr code, but then bind the columns that are needed to the map2_dfr output. Though you still have to drop the names column.

Source https://stackoverflow.com/questions/70329687

QUESTION

If condition with a dataframe

Asked 2021-Nov-21 at 02:39

I want if the conditions are true if df[df["tg"] > 10 and df[df["tg"] < 32 then multiply by five otherwise divide by two. However, I get the following error

ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

...

ANSWER

Answered 2021-Nov-04 at 16:11

Use np.where:

Source https://stackoverflow.com/questions/69842280

QUESTION

Create a new column in a Pandas DataFrame from existing column names

Asked 2021-Nov-15 at 00:22

I want to deconstruct a pandas DataFrame, using column headers as a new data-column and create a list with all combinations of the row index and columns. Easier to show than explain:

...

ANSWER

Answered 2021-Nov-09 at 23:58

The structure that you want your data in is very messy, so this is probably the best method given the data you want.

Source https://stackoverflow.com/questions/69906411

QUESTION

Get min and max values of categorical variable in a dataframe

Asked 2021-Nov-14 at 15:07

I have a dataframe that looks like this:

...

ANSWER

Answered 2021-Nov-13 at 00:30

from itertools import product
aggs = {f"{col}{fn}": (col, fn) for col,fn in product(['X', 'Y', 'Z'], ['min', 'max'])}
df.groupby('D').agg(**aggs)
>>>
   Xmin  Xmax  Ymin  Ymax  Zmin  Zmax
D
A    20    22    16    17    21    23
B    33    34    50    55    11    13
C    44    45    33    34    10    11
D    55    57    34    35    60    61
E    66    67    36    38    13    14

Source https://stackoverflow.com/questions/69950418

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Vulnerabilities

No vulnerabilities reported

Install DataFrame

You can download it from GitHub.

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 .

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