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fix(linting): code formatting
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azory-ydata committed Jul 12, 2024
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Showing 2 changed files with 18 additions and 106 deletions.
104 changes: 8 additions & 96 deletions examples/usaairquality/usaairquality.ipynb
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},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"id": "b514dd38-2ebd-4c96-aed5-4e3695e20fa2",
"metadata": {},
"outputs": [],
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},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"id": "b33a26ed-4e1e-4689-93ce-fa0f98f48e89",
"metadata": {},
"outputs": [],
Expand All @@ -90,7 +90,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"id": "7dab0b47-537d-4402-af71-1bdfd0cf6cdd",
"metadata": {},
"outputs": [],
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},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": null,
"id": "15e613a6",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/fabianaclemente/miniconda3/envs/yprof/lib/python3.11/site-packages/ydata_profiling/visualisation/plot.py:835: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
" df = df.groupby([entity_column, \"__bins\"])[sortbykey].count()\n",
"/Users/fabianaclemente/miniconda3/envs/yprof/lib/python3.11/site-packages/ydata_profiling/visualisation/plot.py:836: FutureWarning: The default value of observed=False is deprecated and will change to observed=True in a future version of pandas. Specify observed=False to silence this warning and retain the current behavior\n",
" df = df.reset_index().pivot_table(entity_column, \"__bins\", sortbykey).T\n"
]
},
{
"data": {
"text/plain": [
"<Axes: xlabel='Time'>"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"outputs": [],
"source": [
"from ydata_profiling.visualisation.plot import timeseries_heatmap\n",
"\n",
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},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"id": "b29a7e78-d52d-458d-ac9a-e509ffd373d1",
"metadata": {},
"outputs": [],
Expand All @@ -203,67 +172,10 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": null,
"id": "7327cb70-3db8-441e-837e-4ac2a5a57eaa",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "ac531d9e9574493083522ec56b68c3cc",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Summarize dataset: 0%| | 0/5 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "6ccba6e512c84b01be36afb26e250000",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Generate report structure: 0%| | 0/1 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"Render widgets: 0%| | 0/1 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "427e682fb36b4017a8f1db4f714bb5e3",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox(children=(Tab(children=(Tab(children=(GridBox(children=(VBox(children=(GridspecLayout(children=(HTML(valu…"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"outputs": [],
"source": [
"profile = ProfileReport(\n",
" group[1],\n",
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20 changes: 10 additions & 10 deletions examples/zero_division.py
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@@ -1,20 +1,20 @@
import pandas as pd
from ydata_profiling import ProfileReport

from ydata_profiling import ProfileReport

if __name__ == '__main__':
if __name__ == "__main__":
import numpy as np

df = pd.read_csv("c6cb4c3d-e735-4b55-bd5c-b7c78ab152aa.csv", sep=',', encoding = "latin")
#df['empty_col'] = [None]*len(df)
df = pd.read_csv(
"c6cb4c3d-e735-4b55-bd5c-b7c78ab152aa.csv", sep=",", encoding="latin"
)
# df['empty_col'] = [None]*len(df)

df.sample(10000)

df.to_csv('Validation.csv')


#df.to_csv('teste.csv')
df.to_csv("Validation.csv")

report = ProfileReport(df, title='Testing the null values')
report.to_file('report.html')
# df.to_csv('teste.csv')

report = ProfileReport(df, title="Testing the null values")
report.to_file("report.html")

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