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but now it's after the "Getting started tutorials".
Also, the examples have diverged a bit, so let's not pretend
that we are creating the same objects.
- [ ] closes #xxxx
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Maybe also extend it to other functions?
Thanks
This works:
```
df1 = pd.DataFrame(np.array([[2,2],[1,1], [0,0]]), columns = ['a1','a2'])
df2 = pd.Series([2,... | {
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- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/33127 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33127/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33127/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33127/events | https://github.com/pandas-dev/pandas/issues/33127 | 589,866,730 | MDU6SXNzdWU1ODk4NjY3MzA= | 33,127 | DataFrame / Series reductions return NaN rather than NA when below min_count | {
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```python
import numpy as np
import pandas as pd
df = pd.DataFrame({"a": [1.0, np.nan]})
print(df.sum(min_count=2))
# a NaN
# dtype: float64
print(df["a"].sum(min_count=2))
# nan
```
but the documentation says we should get `NA` when we're below `min_count`. This kind of gets to the qu... | {
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```python
# It is possible to use anchor suffix for weeks
off1 = pd.tseries.frequencies.to_offset('1W-SUN')
# The anchor does effect when using period_range() or creating a period
ts_start = pd.Timestamp('2020-03-25 10:00') # ts_start is a Wednesday
p1 =... | {
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Documentation issue: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.io.json.build_table_schema.html
(and master branch contains this as well)
Description contains:
```
See _as_json_table_type for conversion types.
```
Which I cannot find anywhere else in the docume... | {
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```python
import pandas as pd
idx = pd.MultiIndex.from_arrays([pd.PeriodIndex([pd.Period("2019Q1"), pd.Period("2019Q2")], name='b')])
idx2 = pd.MultiIndex.from_arrays([idx._get_level_values(level) for leve... | {
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```python
import pandas as pd
from datetime import datetime
mi = pd.MultiIndex.from_product([pd.date_range(datetime.today(), periods=2),
["C", "D"]], names=["alpha", "beta"])
df = pd.DataFrame({"foo": [1, 2, 1, 2], "bar": [1, 2, 3, 4]}, index=mi)
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
Closes #33131, a weakref was released too early. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33136 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33136/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33136/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33136/events | https://github.com/pandas-dev/pandas/issues/33136 | 589,914,762 | MDU6SXNzdWU1ODk5MTQ3NjI= | 33,136 | SeriesGroupBy.quantile doesn't work for nullable integers | {
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import pandas as pd
df = pd.DataFrame(
{"a": ["x", "x", "y", "y"], "b": pd.array([1, 2, 3, 4], dtype="Int64")}
)
df.groupby("a")["b"].quantile(0.5)
```
raises
```python
---------------------------------------------------------------------------
TypeError Traceba... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33137 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33137/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33137/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33137/events | https://github.com/pandas-dev/pandas/pull/33137 | 589,920,696 | MDExOlB1bGxSZXF1ZXN0Mzk1MzQ3NjA5 | 33,137 | BUG: DataFrame.resample raised AmbiguousTimeError at a midnight DST transition | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33141 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33141/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33141/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33141/events | https://github.com/pandas-dev/pandas/issues/33141 | 590,283,617 | MDU6SXNzdWU1OTAyODM2MTc= | 33,141 | Pandas cut method gives an error if labels are non-unique | {
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```python
import pandas as pd
data = pd.DataFrame({'morf':[8142, 8153, 8161]})
bins = [8140, 8150, 8160, 8163]
labels = ['Adenocarcinomas', 'Other specific carcinomas', 'Adenocarcinomas']
data['group'] = pd.cut(data['morf'], bins, labels=labels)
```
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```python
import pandas as pd
dt = {'No': {pd.Timestamp('2020-01-01 00:00:00'): 123,
pd.Timestamp('1900-01-01 00:00:00'): 345,
pd.Timestamp('2017-04-18 00:00:00'): 946,
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```
- [x] doc/source/user_guide/categorical.rst
- [x] doc/source/user_guide/computation.rst
- [x] doc/source/user_guide/cookbook.rst
- [x] doc/source/user_guide/gotchas.rst
- [x] doc/source/user_guide/groupby.rst
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- [x] doc/source/user_guide/reshaping.rst
- [x] doc/source/user_guide/text.rst
- [x] doc/source/user_guide/timeseries.rst
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However, currently, there is not always a guarantee that the result will actually be a scalar. For example, with a Seri... | {
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```python
# This works:
df1 = df.resample(to_freq,
closed='left',
kind='period',
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('Close', 'last'),
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Started as a CLN branch and i left that in for now, can separate if desired. the bugfix is on L287. | {
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... | 3 | 2020-03-31T02:01:18Z | 2020-05-22T03:45:14Z | null | MEMBER | null | #33148 introduced an empty_frame fixture in the top level conftest. At the same time, we have a lot of `... = DataFrame()` assignments in our tests. We should standardize to use the fixture where appropriate | {
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] | closed | false | null | [] | null | 1 | 2020-03-31T02:12:31Z | 2020-03-31T03:13:39Z | 2020-03-31T03:13:32Z | NONE | null | Hi all,
I am trying to create rolling values from a function that returns a numpy value, to get an idea of how stable to value is over time
see my below attempt
' ' 'python
array([-9.51263882e-03, -2.81717483e-02, 9.43949087e-05, ...,
-9.07504803e-03, -4.77400512e-03, 1.51740085e-03])
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Any of my attempts at using `io.BytesIO` failed.
This can be useful for applications where the bytes of the resulting HDF file need to be sent over the network. | {
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Maybe **not a high priority bug**, but I have the feeling it can easily fixed. I just have not enough understanding on how it should be fixed. Please find below the MCVE to reproduce it:
```
import numpy as np
import pandas as pd
# Sample Dataset:
n = 20... | {
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---
I'll revert any change related to styling, I applied "black" formatting in some places, just so I could think straight. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33170 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33170/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33170/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33170/events | https://github.com/pandas-dev/pandas/issues/33170 | 590,925,081 | MDU6SXNzdWU1OTA5MjUwODE= | 33,170 | Feature request: convert period to timedelta | {
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```python
import pandas as pd
mPI = pd.period_range(start='2020-02-01 10:00', end='2020-05-20 10:00', freq='1M')
mPI[0]
>>> Period('2020-02', 'M')
td = pd.Timedelta(mPI[0])
>>> ValueError: Value must be Timedelta, string, integer, float, timedelta or ... | {
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```python
import pandas as pd
periods = 7
start = '20100131'
dates = pd.date_range(start=start, freq='M', periods=periods)
df = pd.DataFrame(range(periods), index=dates, columns=['a'])
print('Original: freq="M"')
print(df)
print('\n-> "b" -> "BM"')
p... | {
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```python
pd.Series(list("abcde"), dtype="string").value_counts(normalize=True)
```
```bash
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-40-718821f804b4> in <module>
... | {
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```python
import pandas as pd
import numpy as np
df = pd.DataFrame(dict(zip(['A', 'B'], np.random.randn(2, 100))))
df.plot.hist(weights=0.1*np.ones(shape=(100, 2))) # fail
```
#### Problem description
Trying to plot a histogram of a multi-column data fram... | {
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- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/33180 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33180/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33180/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33180/events | https://github.com/pandas-dev/pandas/pull/33180 | 591,125,065 | MDExOlB1bGxSZXF1ZXN0Mzk2MzQ4NzI3 | 33,180 | BUG: support min/max functions for rolling windows with custom BaseIndexer | {
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- [X] 1 tests added / 1 passed
- [X] passes `black pandas`
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## The problem
We currently don't support several rolling window functions when building a rolling window object using a custom class descended ... | {
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import numpy as np
from sklearn.svm import SVR
from sklearn.linear_model import LinearRegression
import matplotlib.pyplot as plt
df1 = pd.read_excel("npl90.xlsx",parse_dates=True)
dates = []
npl = []
df1.shape
df=df1.iloc[::-1]
df.tail(1)
df=df.head(len(df)-1)
df
df_dates=df.loc[:, ... | {
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### Background
`sparse` implements a sparse ndarray that implements (much of) the NumPy API. This differs from `scipy... | {
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- [X] tests added / passed
- [X] passes `black pandas`
- [X] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
Raises a `ValueError` on version 0.25.1 (reporter's version), as expected:
```
>>> import pandas as pd
>>> pd.__version__
'0.25.1'
>>> ser = ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33186 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33186/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33186/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33186/events | https://github.com/pandas-dev/pandas/issues/33186 | 591,288,778 | MDU6SXNzdWU1OTEyODg3Nzg= | 33,186 | pandas >= 1.0.0 fails to read an old HDF5 file | {
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... | open | false | null | [] | null | 4 | 2020-03-31T17:31:53Z | 2020-09-10T00:19:07Z | null | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
import pandas as pd
pd.read_hdf("beads1.h5", "features")
```
#### Problem description
While working on pandas 0.25, this fails starting with pandas 1.0.0. The HDF file was created in November 2015 or even earlier and is inside the [zip file](http... | {
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----
> I recall this being mentioned on one of the core dev calls a few months back, and took inspiration from [rapidsai/cudf](https://github.com/rapidsai/cudf) for the various templates.
>
> Added templates for the following use cases:
>
> * Bug Report... | {
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With [data.csv.txt](https://github.com/pandas-dev/pandas/files/4410722/data.csv.txt):
```python
>>> pd.read_csv('/tmp/data.csv.txt') # header='infer' default
1540 125205 PRODAJA 04-JUN-18 -3 -.625 -.726
0 1540 125205 PRODAJA 29-JUN-18 -1.00 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33190 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33190/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33190/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33190/events | https://github.com/pandas-dev/pandas/pull/33190 | 591,479,978 | MDExOlB1bGxSZXF1ZXN0Mzk2NjQ3Mjgw | 33,190 | CLN: Correct docstring to describe actual functionality. | {
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```python
from datetime import datetime
from pandas.tseries.offsets import QuarterBegin
now = datetime.datetime(2020, 1, 12)
now - QuarterBegin()
```
#### Problem description
The code shows the following results:
now - QuarterBegin()
Out[28]: Tim... | {
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Enhancement proposal
```python
>>> df.to_csv('data.csv.gz') # Awfully slow
>>> df.to_pickle('data.pkl.bz2') # Awfully slow
>>> df.to_csv('data.csv.gz', fast=True) # Uses fast compressionlevel=1
# or, better:
>>> pd.options.io.compressionlevel =... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33198 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33198/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33198/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33198/events | https://github.com/pandas-dev/pandas/issues/33198 | 591,601,876 | MDU6SXNzdWU1OTE2MDE4NzY= | 33,198 | BUG: iloc setting columns not taking effect | {
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arr = np.random.randn(10 ** 6).reshape(500, 2000).astype(np.float64)
df = pd.DataFrame(arr)
df.iloc[:, 1000:] = df.iloc[:, 1000:].astype(np.float32)
>>> df.dtypes.value_counts()
float64 2000
dtype: int64
```
I would expect 1000 float64 columns and 1000 float32 columns. I get the expected behavior if... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33199 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33199/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33199/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33199/events | https://github.com/pandas-dev/pandas/pull/33199 | 591,655,557 | MDExOlB1bGxSZXF1ZXN0Mzk2NzgyNDMx | 33,199 | DOC: Fix Error in pandas.Series.last | {
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- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
Related to #27977.
output of `python scripts/validate_docstrings.py pandas.Series.last`:
```
##################################################... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33200 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33200/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33200/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33200/events | https://github.com/pandas-dev/pandas/issues/33200 | 591,667,302 | MDU6SXNzdWU1OTE2NjczMDI= | 33,200 | BUG: 'groupby()' results in shifted results for 'quantile()' | {
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"followers_url": "https://api.github.c... | 4 | 2020-04-01T06:41:12Z | 2020-05-25T21:58:07Z | 2020-05-25T21:58:07Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
# Imports
import pandas as pd
import numpy as np
# Define x and bins
x = np.linspace(0, 1, 100)
bins = np.arange(0, 1, 0.1)
# Create Series object with the x-data
series = pd.Series(x, name='X')
# Group series by provided bins
data_cut =... | {
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During my work on generalizing our rolling window functions, @mroeschke and @jreback have pointed out that it would be useful to expose a couple `BaseIndexer` subclasses as a part of our api (in pandas.api.indexers, to be specific). For instance, forward-looking windows are fairly common in s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33202 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33202/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33202/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33202/events | https://github.com/pandas-dev/pandas/issues/33202 | 591,787,530 | MDU6SXNzdWU1OTE3ODc1MzA= | 33,202 | row sum and column mean works but row mean gives all NaN, on heterogenous data types | {
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```
df=pd.DataFrame({'a':[1,pd.to_timedelta('1D'),3.], 'b':[4,pd.to_timedelta('1.5D'),6.], 'c':[7,pd.to_timedelta('0.5D'),np.nan]})
# df=pd.DataFrame({'a':[1,2,3.], 'b':[4,5,6.], 'c':[7,8,np.nan]})
display(df.tr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33203 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33203/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33203/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33203/events | https://github.com/pandas-dev/pandas/issues/33203 | 591,825,824 | MDU6SXNzdWU1OTE4MjU4MjQ= | 33,203 | STY/TST: what standard to follow to import top-level objects in tests | {
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In test code, do we do:
```
from pandas import Series
...
Series(...)
```
or
```
import pandas as pd
...
pd.Series(..)
```
Personally, ... | {
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I added a test for the issue 24615. | {
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```
dtypes = {
'created': 'int64',
'eventType' : 'category',
'severity' : 'category'
}
df = pd.read_json('dataset.json', lines=True, dtype=dtypes)
df.info()
```
Results into:
```
created int64
eventType object
severi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33206 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33206/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33206/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33206/events | https://github.com/pandas-dev/pandas/issues/33206 | 591,933,185 | MDU6SXNzdWU1OTE5MzMxODU= | 33,206 | ENH: Add accessor for isocalendar returning iso year, week, and day | {
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Currently, we can access the ISO week via `week` and `weekofyear`, *and* `Timestamp` objects provide `isocalendar`, which returns the correct ISO year, week, a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33207 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33207/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33207/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33207/events | https://github.com/pandas-dev/pandas/issues/33207 | 591,938,156 | MDU6SXNzdWU1OTE5MzgxNTY= | 33,207 | Everything works fine | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33208 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33208/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33208/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33208/events | https://github.com/pandas-dev/pandas/pull/33208 | 591,981,119 | MDExOlB1bGxSZXF1ZXN0Mzk3MDQ5MTI1 | 33,208 | DOC: Fixed examples in pandas/core/indexes/ | {
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- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/33209 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33209/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33209/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33209/events | https://github.com/pandas-dev/pandas/issues/33209 | 591,996,882 | MDU6SXNzdWU1OTE5OTY4ODI= | 33,209 | API/BUG: isna_old on EAs? | {
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"followers_url": "https://api.github.com/users/j... | 2 | 2020-04-01T15:17:51Z | 2020-05-10T18:50:58Z | 2020-05-10T18:50:57Z | MEMBER | null | isna_new has a code path that handles EAs that isna_old doesnt, so the following will raise:
```
pd.set_option("mode.use_inf_as_na", True)
pd.isna(my_decimal_array)
```
Most of this can be fixed by adding to isna_ndarray_old:
```
if is_extension_array_dtype(values.dtype):
result = values.isna()
```
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https://api.github.com/repos/pandas-dev/pandas/issues/33210 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33210/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33210/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33210/events | https://github.com/pandas-dev/pandas/issues/33210 | 591,997,838 | MDU6SXNzdWU1OTE5OTc4Mzg= | 33,210 | MacPython/pandas-wheels wheel builds failing | {
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"followers_url": "https://api.github.com/users/j... | 6 | 2020-04-01T15:19:08Z | 2020-04-28T22:54:21Z | 2020-04-28T22:54:21Z | CONTRIBUTOR | null | This affects the linux builds, both py37 and py38, 32 or 64-bit.
https://dev.azure.com/pandas-dev/pandas-wheels/_build/results?buildId=30996&view=logs&j=517fe804-fa30-5dc2-1413-330699242c05&t=2e128ad5-2f7f-5333-3f34-c85b8fbc7250&l=1216
```
=================================== FAILURES ============================... | {
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... | null | 6 | 2020-04-01T18:00:21Z | 2020-04-16T23:11:21Z | 2020-04-16T23:11:21Z | CONTRIBUTOR | null | - [x] xref #32316
- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
As suggested by @datapythonista , I've added checks in `ci/code_checks.sh` to look if the pandas is being referenced in a standardized way i.e pandas,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/33215 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/33215/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/33215/comments | https://api.github.com/repos/pandas-dev/pandas/issues/33215/events | https://github.com/pandas-dev/pandas/issues/33215 | 592,114,700 | MDU6SXNzdWU1OTIxMTQ3MDA= | 33,215 | [PROPOSAL] Make Series.update() accept a dictionary | {
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I propose to re-write the `Series.update() ` method to accept a dictionary object. This would be useful for example when you are iterating over a DataFrame using `DataFrame.iterrows()`, and you want to update the `row` object returned by `iterrows()` in order to ... | {
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- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
---
This is needed for the check in #32942 to ignore cython files. | {
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