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Added Pandas Kurtosis & Pandas Skew nodes. Fixed docstrings for various nodes to address doc inaccuracies from v1.1.0 changes.

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HowToSD
2025-02-22 03:50:06 -08:00
parent c411d95431
commit 6b4f62d2c2
22 changed files with 266 additions and 18 deletions
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__init__.py
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@@ -47,6 +47,7 @@ from .modules.pandas_wrapper.pandas_index import PandasIndex
from .modules.pandas_wrapper.pandas_index_to_string import PandasIndexToString
from .modules.pandas_wrapper.pandas_isna import PandasIsNA
from .modules.pandas_wrapper.pandas_join import PandasJoin
from .modules.pandas_wrapper.pandas_kurtosis import PandasKurtosis
from .modules.pandas_wrapper.pandas_load_csv import PandasLoadCSV
from .modules.pandas_wrapper.pandas_load_csv_with_encoding import PandasLoadCSVWithEncoding
from .modules.pandas_wrapper.pandas_load_csv_with_index import PandasLoadCSVWithIndex
@@ -83,6 +84,7 @@ from .modules.pandas_wrapper.pandas_show_index import PandasShowIndex
from .modules.pandas_wrapper.pandas_show_series import PandasShowSeries
from .modules.pandas_wrapper.pandas_show_text import PandasShowText
from .modules.pandas_wrapper.pandas_sin import PandasSin
from .modules.pandas_wrapper.pandas_skew import PandasSkew
from .modules.pandas_wrapper.pandas_sort import PandasSort
from .modules.pandas_wrapper.pandas_std import PandasStd
from .modules.pandas_wrapper.pandas_sub import PandasSub
@@ -154,6 +156,7 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"PandasIndexToString": PandasIndexToString,
"PandasIsNA": PandasIsNA,
"PandasJoin": PandasJoin,
"PandasKurtosis": PandasKurtosis,
"PandasLoadCSV": PandasLoadCSV,
"PandasLoadCSVWithEncoding": PandasLoadCSVWithEncoding,
"PandasLoadCSVWithIndex": PandasLoadCSVWithIndex,
@@ -190,6 +193,7 @@ NODE_CLASS_MAPPINGS: Dict[str, Type[T]] = {
"PandasShowSeries": PandasShowSeries,
"PandasShowText": PandasShowText,
"PandasSin": PandasSin,
"PandasSkew": PandasSkew,
"PandasSort": PandasSort,
"PandasStd": PandasStd,
"PandasSub": PandasSub,
@@ -261,6 +265,7 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"PandasIndexToString": "Pandas Index To String",
"PandasIsNA": "Pandas Is NA",
"PandasJoin": "Pandas Join",
"PandasKurtosis": "Pandas Kurtosis",
"PandasLoadCSV": "Pandas Load CSV",
"PandasLoadCSVWithEncoding": "Pandas Load CSV With Encoding",
"PandasLoadCSVWithIndex": "Pandas Load CSV With Index",
@@ -297,6 +302,7 @@ NODE_DISPLAY_NAME_MAPPINGS: Dict[str, str] = {
"PandasShowSeries": "Pandas Show Series",
"PandasShowText": "Pandas Show Text",
"PandasSin": "Pandas Sin",
"PandasSkew": "Pandas Skew",
"PandasSort": "Pandas Sort",
"PandasStd": "Pandas Std",
"PandasSub": "Pandas Sub",
docs/reference/node_reference.md
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@@ -114,11 +114,13 @@
| [Pandas Corr](pandas_corr.md) | Computes the correlation of the DataFrame. You can select from the Pearson, Kendall or Spearman methods. |
| [Pandas Count](pandas_count.md) | Computes the count of a pandas DataFrame. |
| [Pandas Cov](pandas_cov.md) | Computes the covariance of the DataFrame. |
| [Pandas Kurtosis](pandas_kurtosis.md) | Computes the unbiased kurtosis of the DataFrame. |
| [Pandas Max](pandas_max.md) | Computes the max of a pandas DataFrame. |
| [Pandas Mean](pandas_mean.md) | Computes the mean of a pandas DataFrame. |
| [Pandas Median](pandas_median.md) | Computes the median of a pandas DataFrame. |
| [Pandas Min](pandas_min.md) | Computes the min of a pandas DataFrame. |
| [Pandas Mode](pandas_mode.md) | Computes the mode of a pandas DataFrame. |
| [Pandas Skew](pandas_skew.md) | Computes the unbiased skewness of the DataFrame. |
| [Pandas Std](pandas_std.md) | Computes the standard deviation of a pandas DataFrame. |
| [Pandas Sum](pandas_sum.md) | Computes the sum of a pandas DataFrame. |
| [Pandas Summary](pandas_summary.md) | Analyzes and summarizes a pandas DataFrame. |
docs/reference/pandas_kurtosis.md
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@@ -0,0 +1,22 @@
# Pandas Kurtosis
Computes the unbiased kurtosis of the DataFrame.
This method returns the excess kurtosis rather than the raw kurtosis.
Excess kurtosis is calculated by subtracting 3 from the raw kurtosis,
which offsets it relative to the kurtosis of a normal distribution.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| axis | |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Summary statistics
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
docs/reference/pandas_skew.md
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@@ -0,0 +1,18 @@
# Pandas Skew
Computes the unbiased skewness of the DataFrame.
## Input
| Name | Data type |
|---|---|
| dataframe | DataFrame |
| axis | |
## Output
| Data type |
|---|
| DataFrame |
<HR>
Category: Summary statistics
ComfyUI Data Analysis Node Reference. © 2025 Hide Inada (HowToSD.com). All rights reserved.
examples/datasets/random_data.csv
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@@ -0,0 +1,101 @@
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56 1.030999522495951 171.4653623664934 -0.2596849829770067 0.08483771408519192
57 0.9312801191161986 166.42824290986817 0.25788296356687435 0.9866395785011755
58 -0.8392175232226385 179.3288725557238 1.1334555745933113 0.3742707957561203
59 -0.3092123758512146 172.36916460455893 0.14616526719060963 0.3706421470668909
60 0.33126343140356396 164.04348251398676 0.7219097140731142 0.8127995672575026
61 0.9755451271223592 173.28276804316914 0.8873170267146684 0.9472485773838587
62 -0.47917423784528995 165.12659164886338 0.036534764210958526 0.9860010638228709
63 -0.18565897666381712 173.93542301871227 0.47023732196909995 0.7533781852589416
64 -1.1063349740060282 175.792977895037 -1.1206336700345363 0.37625958553091576
65 -1.1962066240806708 165.89658840824146 -0.012193820667144917 0.08350071669866876
66 0.812525822394198 174.81688064622162 0.3737159243034198 0.7771469159274368
67 1.356240028570823 172.0639046346825 -0.12389159098242475 0.558404249735805
68 -0.07201012158033385 174.11030079997244 1.3162056519658176 0.4242220092469763
69 1.0035328978920242 179.48396491326974 -0.21507068898031634 0.906354385094736
70 0.36163602504763415 168.77305941998566 0.27997775665150815 0.11119748230615134
71 -0.6451197546051243 166.23131917821254 0.5653702886430456 0.49262510429085915
72 0.36139560550841393 165.55242785187238 1.2206366445330579 0.011353644767419069
73 1.5380365664659692 165.92094857517282 -0.2179310755897197 0.46866064199412627
74 -0.03582603910995154 169.61449145292949 1.0815818760774798 0.05630327568183735
75 1.5646436558140062 171.7057598740832 0.5051165305097935 0.11881791626807192
76 -2.6197451040897444 171.3834539966501 0.009245674476024535 0.11752624677710488
77 0.8219025043752238 174.1359162451801 0.7310517371316354 0.6492103021160636
78 0.08704706823817122 170.06500945938953 0.599529847786735 0.7460448792654233
79 -0.29900735046586746 177.26767038578657 0.19989156142060266 0.5833687650971596
80 0.0917607765355023 168.67671583381022 0.5349010424950095 0.9621725484745419
81 -1.9875689146008928 183.6008458329481 0.3073432015691199 0.37487057952370406
82 -0.21967188783751193 173.12833673882503 0.5567586726256241 0.28571208628186073
83 0.3571125715117464 165.7142122179186 0.8310653372605233 0.8685991281894603
84 1.477894044741516 164.64553750969444 1.293008408072676 0.22359583851945264
85 -0.5182702182736474 172.4123620762159 -0.11890774941342452 0.9632225394406113
86 -0.8084936028931876 168.88268607337073 1.5665166873281333 0.012154474689816341
87 -0.5017570435845365 173.57000247046045 -0.47604389976125094 0.969878826707639
88 0.9154021177020741 172.36618812286773 0.4241074524822083 0.04315991195057611
89 0.32875110965968446 169.63585543671564 0.7941586032422883 0.8911431136980711
90 -0.5297602037670388 165.76603140965798 0.6404959338675164 0.5277011090862999
91 0.5132674331133561 162.42576387657067 0.1886502400897031 0.9929647961193003
92 0.09707754934804039 167.7674252396649 0.39593887482136236 0.07379656473539886
93 0.9686449905328892 174.28199397161737 0.25349953267058356 0.5538542844013208
94 -0.7020530938773524 171.070468720651 0.20531762152789423 0.969302535619099
95 -0.3276621465977682 163.77130610644005 0.9248010485105123 0.5230978441701488
96 -0.39210815313215763 170.8659046292559 0.6785077429825237 0.6293986381352625
97 -1.4635149481321186 171.9265868986442 0.1535452023696729 0.6957486889846172
98 0.29612027706457605 165.58071281899433 0.9497999377166253 0.45454106476777323
99 0.26105527217988933 170.76862552972764 0.6536497604383047 0.6275580800840634
100 0.00511345664246089 170.29104359223 0.90643105941948 0.5843143119231002
101 -0.23458713337514692 164.28514851084688 0.8148144209618061 0.901158010490989
modules/pandas_wrapper/pandas_create.py
+2 -2
View File
@@ -30,13 +30,13 @@ class PandasCreate:
def create(self, data: str) -> tuple:
"""
Create a pandas DataFrame using values entered in the text field and converts it to a JSON string.
Create a pandas DataFrame using values entered in the text field and converts it to a DataFrame.
Args:
data (str): String value in the text field.
Returns:
tuple: A tuple containing a JSON string representation of the DataFrame.
tuple: A tuple containing a the DataFrame.
"""
# Read CSV file into DataFrame
df = pd.read_csv(StringIO(data))
modules/pandas_wrapper/pandas_create_with_index.py
+2 -2
View File
@@ -31,7 +31,7 @@ class PandasCreateWithIndex:
def create(self, data: str, index_col: int=0) -> tuple:
"""
Create a pandas DataFrame using values entered in the text field and converts it to a JSON string.
Create a pandas DataFrame using values entered in the text field and converts it to a DataFrame.
Input data is assume to have an index.
Args:
@@ -39,7 +39,7 @@ class PandasCreateWithIndex:
index_col (int): Position of the index column.
Returns:
tuple: A tuple containing a JSON string representation of the DataFrame.
tuple: A tuple containing the DataFrame.
"""
# Read CSV file into DataFrame
df = pd.read_csv(StringIO(data), index_col=index_col)
modules/pandas_wrapper/pandas_cummax.py
+1 -1
View File
@@ -37,7 +37,7 @@ class PandasCummax:
axis (str): Specify the direction to compute: Index (row label) or column label.
Returns:
tuple: A tuple containing a JSON string of the renamed DataFrame.
tuple: A tuple containing the DataFrame.
"""
if axis=="index":
df_out = dataframe.cummax(axis=0)
modules/pandas_wrapper/pandas_cummin.py
+1 -1
View File
@@ -37,7 +37,7 @@ class PandasCummin:
axis (str): Specify the direction to compute: Index (row label) or column label.
Returns:
tuple: A tuple containing a JSON string of the renamed DataFrame.
tuple: A tuple containing the DataFrame.
"""
if axis=="index":
df_out = dataframe.cummin(axis=0)
modules/pandas_wrapper/pandas_cumprod.py
+1 -1
View File
@@ -37,7 +37,7 @@ class PandasCumprod:
axis (str): Specify the direction to compute: Index (row label) or column label.
Returns:
tuple: A tuple containing a JSON string of the renamed DataFrame.
tuple: A tuple containing the DataFrame.
"""
if axis=="index":
df_out = dataframe.cumprod(axis=0)
modules/pandas_wrapper/pandas_cumsum.py
+1 -1
View File
@@ -37,7 +37,7 @@ class PandasCumsum:
axis (str): Specify the direction to compute: Index (row label) or column label.
Returns:
tuple: A tuple containing a JSON string of the renamed DataFrame.
tuple: A tuple containing the DataFrame.
"""
if axis=="index":
df_out = dataframe.cumsum(axis=0)
modules/pandas_wrapper/pandas_group_by.py
+1 -1
View File
@@ -44,7 +44,7 @@ class PandasGroupBy:
aggregate_function (str): The type of aggregate function to perform.
Returns:
tuple: A tuple containing a JSON string of the merged DataFrame.
tuple: A tuple containing the merged DataFrame.
"""
if aggragate_function == "max":
df_out = dataframe.groupby(column_name).max()
modules/pandas_wrapper/pandas_head.py
+1 -1
View File
@@ -38,7 +38,7 @@ class PandasHead:
rows (int): The number of rows to retrieve.
Returns:
tuple: A tuple containing a JSON string of the resulting DataFrame.
tuple: A tuple containing the resulting DataFrame.
"""
df2 = dataframe.head(rows)
return (df2,)
modules/pandas_wrapper/pandas_iloc_rows_dataframe.py
+1 -2
View File
@@ -43,8 +43,7 @@ class PandasIlocRowsDataFrame:
row_int_pos_list_json (str): A list containing row integer positions.
Returns:
tuple: A tuple containing the value of the row in string. The string is
a JSON string containing the serialized Pandas Series object.
tuple: A tuple containing the DataFrame.
"""
row_int_pos_list = json.loads(row_int_pos_list_json)
df2 = dataframe.iloc[row_int_pos_list]
modules/pandas_wrapper/pandas_join.py
+1 -1
View File
@@ -42,7 +42,7 @@ class PandasJoin:
join_method (str): The type of join to perform ("inner", "left", "right", "outer").
Returns:
tuple: A tuple containing a JSON string of the merged DataFrame.
tuple: A tuple containing the merged DataFrame.
"""
df_out = pd.merge(left_dataframe, right_dataframe, on=on_column_name, how=join_method)
return (df_out,)
modules/pandas_wrapper/pandas_kurtosis.py
+52
View File
@@ -0,0 +1,52 @@
from typing import Any, Dict
import pandas as pd
class PandasKurtosis:
"""
Computes the unbiased kurtosis of the DataFrame.
This method returns the excess kurtosis rather than the raw kurtosis.
Excess kurtosis is calculated by subtracting 3 from the raw kurtosis,
which offsets it relative to the kurtosis of a normal distribution.
category: Summary statistics
"""
@classmethod
def INPUT_TYPES(cls) -> Dict[str, Any]:
"""
Defines the input types for the function.
Returns:
Dict[str, Any]: A dictionary specifying required input types.
"""
return {
"required": {
"dataframe": ("DATAFRAME", {}),
"axis": (("index", "columns"),),
}
}
RETURN_TYPES: tuple = ("PDSERIES",)
FUNCTION: str = "f"
CATEGORY: str = "Data Analysis"
def f(self, dataframe: pd.DataFrame, axis: str) -> tuple:
"""
Computes the unbiased kurtosis of the DataFrame.
Args:
dataframe (DataFrame): The DataFrame.
axis (str): Specify the direction to compute: Index (row label) or column label.
Returns:
tuple: A tuple containing the series.
"""
if axis=="index":
series = dataframe.kurtosis(axis=0)
elif axis=="columns":
series = dataframe.kurtosis(axis=1)
else:
raise ValueError("Invalid axis. Only index or columns are supported.")
return (series,)
modules/pandas_wrapper/pandas_rename.py
+1 -1
View File
@@ -45,7 +45,7 @@ class PandasRename:
new_label (str): The new label.
Returns:
tuple: A tuple containing a JSON string of the renamed DataFrame.
tuple: A tuple containing the DataFrame.
"""
if axis=="index":
df_out = dataframe.rename(index={current_label:new_label})
modules/pandas_wrapper/pandas_select_rows.py
+1 -1
View File
@@ -37,7 +37,7 @@ class PandasSelectRows:
condition (str): A string representing the condition to filter rows.
Returns:
tuple: A tuple containing a JSON string of the filtered DataFrame.
tuple: A tuple containing the filtered DataFrame.
"""
# Apply condition
df2 = dataframe.query(condition)
modules/pandas_wrapper/pandas_skew.py
+48
View File
@@ -0,0 +1,48 @@
from typing import Any, Dict
import pandas as pd
class PandasSkew:
"""
Computes the unbiased skewness of the DataFrame.
category: Summary statistics
"""
@classmethod
def INPUT_TYPES(cls) -> Dict[str, Any]:
"""
Defines the input types for the function.
Returns:
Dict[str, Any]: A dictionary specifying required input types.
"""
return {
"required": {
"dataframe": ("DATAFRAME", {}),
"axis": (("index", "columns"),),
}
}
RETURN_TYPES: tuple = ("PDSERIES",)
FUNCTION: str = "f"
CATEGORY: str = "Data Analysis"
def f(self, dataframe: pd.DataFrame, axis: str) -> tuple:
"""
Computes the unbiased skewness of the DataFrame.
Args:
dataframe (DataFrame): The DataFrame.
axis (str): Specify the direction to compute: Index (row label) or column label.
Returns:
tuple: A tuple containing the series.
"""
if axis=="index":
series = dataframe.skew(axis=0)
elif axis=="columns":
series = dataframe.skew(axis=1)
else:
raise ValueError("Invalid axis. Only index or columns are supported.")
return (series,)
modules/pandas_wrapper/pandas_sort.py
+1 -1
View File
@@ -39,7 +39,7 @@ class PandasSort:
ascending (bool): Whether to sort in ascending order.
Returns:
tuple: A tuple containing a JSON string of the sorted DataFrame.
tuple: A tuple containing the sorted DataFrame.
"""
df2 = dataframe.sort_values(by=column_name, ascending=ascending)
return (df2,)
modules/pandas_wrapper/pandas_transpose.py
+1 -1
View File
@@ -34,6 +34,6 @@ class PandasTranspose:
dataframe (DataFrame): The DataFrame.
Returns:
tuple: A tuple containing a JSON string of the transposed DataFrame.
tuple: A tuple containing the transposed DataFrame.
"""
return (dataframe.transpose(),)
pyproject.toml
+1 -1
View File
@@ -1,7 +1,7 @@
[project]
name = "data-analysis"
description = "Data analysis custom modules for ComfyUI - Use Pandas & Matplotlib within ComfyUI"
version = "1.1.19"
version = "1.1.20"
license = {file = "LICENSE"}
[project.urls]