dataframe | A package to manage R-like data frames written in Go
kandi X-RAY | dataframe Summary
kandi X-RAY | dataframe Summary
A package to manage R-like data frames written in Go. For an example, visit the example sub-directory.
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Top functions reviewed by kandi - BETA
- Main entry point .
- ReadDataFrame reads a data frame from an io . Reader
- Next returns the next data frame
- ReadDataSet reads a DataSet from an io . Reader .
- ReadDataSetFile reads a DataSet from a file .
- ReadDataFrameFile reads a data frame file .
dataframe Key Features
dataframe Examples and Code Snippets
Community Discussions
Trending Discussions on dataframe
QUESTION
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:
...ANSWER
Answered 2022-Jan-24 at 16:57Create 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
QUESTION
ANSWER
Answered 2022-Mar-21 at 14:44Does this work for you?
QUESTION
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 06:41I 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.
QUESTION
The following code:
...ANSWER
Answered 2022-Feb-13 at 19:56From 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:
QUESTION
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.
ANSWER
Answered 2021-Sep-12 at 20:24This should do the job. String match with Levenshtein_distance.
pip install thefuzz[speedup]
QUESTION
I've this situation:
...ANSWER
Answered 2021-Dec-26 at 20:48We may use read.dcf
from base R
QUESTION
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:
...ANSWER
Answered 2021-Dec-13 at 04:44One 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.
QUESTION
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 16:11Use np.where
:
QUESTION
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 23:58The structure that you want your data in is very messy, so this is probably the best method given the data you want.
QUESTION
I have a dataframe that looks like this:
...ANSWER
Answered 2021-Nov-13 at 00:30from 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
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