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Currently covering the most popular Java, JavaScript and Python libraries. See a SAMPLE HERE.
kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
:seedling: Repositório com projetos de teste e notas de estudo
Vuetify: My navigation drawer is positioned over another element (toolbar)
Add clipped to v-navigation-drawer props like:
<v-navigation-drawer
clipped>
<!-- ... -->
</v-navigation-drawer>
How to sort/order a list according to time in 00:00 format?
void main() {
json.sort((x, y) => '${x['time']}'.seconds.compareTo('${y['time']}'.seconds));
for (final element in json) {
print(element);
}
}
final json = [
{'id': 1, 'time': '10:00:01'},
{'id': 3, 'time': '30:00'},
{'id': 2, 'time': '20:00'},
{'id': 4, 'time': '40:00'},
{'id': 0, 'time': '10:00'},
];
extension _Time on String {
int get seconds {
var hours = 0;
var minutes = 0;
var seconds = 0;
final parts = split(':');
switch (parts.length) {
case 2:
minutes = _toInt(parts[0], 59);
seconds = _toInt(parts[1], 59);
break;
case 3:
hours = _toInt(parts[0], 23);
minutes = _toInt(parts[1], 59);
seconds = _toInt(parts[2], 59);
break;
default:
_error();
}
return hours * 3600 + minutes * 60 + seconds;
}
void _error() {
throw FormatException('Invalid time format: $this');
}
int _toInt(String part, int max) {
final result = int.tryParse(part, radix: 10);
if (result == null) {
_error();
}
if (result < 0 || result > max) {
_error();
}
return result;
}
}
{id: 0, time: 10:00}
{id: 1, time: 10:00:01}
{id: 2, time: 20:00}
{id: 3, time: 30:00}
{id: 4, time: 40:00}
-----------------------
void main() {
json.sort((x, y) => '${x['time']}'.seconds.compareTo('${y['time']}'.seconds));
for (final element in json) {
print(element);
}
}
final json = [
{'id': 1, 'time': '10:00:01'},
{'id': 3, 'time': '30:00'},
{'id': 2, 'time': '20:00'},
{'id': 4, 'time': '40:00'},
{'id': 0, 'time': '10:00'},
];
extension _Time on String {
int get seconds {
var hours = 0;
var minutes = 0;
var seconds = 0;
final parts = split(':');
switch (parts.length) {
case 2:
minutes = _toInt(parts[0], 59);
seconds = _toInt(parts[1], 59);
break;
case 3:
hours = _toInt(parts[0], 23);
minutes = _toInt(parts[1], 59);
seconds = _toInt(parts[2], 59);
break;
default:
_error();
}
return hours * 3600 + minutes * 60 + seconds;
}
void _error() {
throw FormatException('Invalid time format: $this');
}
int _toInt(String part, int max) {
final result = int.tryParse(part, radix: 10);
if (result == null) {
_error();
}
if (result < 0 || result > max) {
_error();
}
return result;
}
}
{id: 0, time: 10:00}
{id: 1, time: 10:00:01}
{id: 2, time: 20:00}
{id: 3, time: 30:00}
{id: 4, time: 40:00}
C# - Entity Framework Code first, lazy loading not working
[ForeignKey("idProgramas")]
public virtual Programas Programas { get; set; }
[ForeignKey("idProjetos")]
public virtual Projetos Projetos { get; set; }
db.Estudos
.Include(x => x.Programas)
.Include(x => x.Projetos)
.ToList();
-----------------------
[ForeignKey("idProgramas")]
public virtual Programas Programas { get; set; }
[ForeignKey("idProjetos")]
public virtual Projetos Projetos { get; set; }
db.Estudos
.Include(x => x.Programas)
.Include(x => x.Projetos)
.ToList();
Conditionally render JSX on specific routes
import React from 'react';
import { Link, useLocation, useHistory, withRouter } from 'react-router-dom';
import logoImg from '../../assets/images/logo.svg';
import backIcon from '../../assets/images/icons/back.svg';
import './styles.css';
function SplitScreen(props: { children: React.ReactNode; }) {
const { pathname } = useLoction();
const showBack = !pathname.startsWith("/login");
return (
<section className="split-page-container">
<div className="right-side">
{showBack && (
<Link
className="back-arrow"
to="/">
<img src={backIcon} alt="Voltar" />
</Link>
)}
<div className="proffy">
<div className="proffy-fundo">
<img src={logoImg} alt="Proffy Logo" />
<h2>Sua plataforma de <br /> estudos online.</h2>
</div>
</div>
</div>
<div className="left-side">
<div className="content-box">
{props.children}
</div>
</div>
</section>
);
}
function SplitScreen(props: { children: React.ReactNode; }) {
const { pathname } = useLoction();
const showBack = !pathname.startsWith("/login");
return (
<section className="split-page-container">
<div className="left-side"> // <-- now the left side
{showBack && (
<Link
className="back-arrow"
to="/">
<img src={backIcon} alt="Voltar" />
</Link>
)}
<div className="proffy">
<div className="proffy-fundo">
<img src={logoImg} alt="Proffy Logo" />
<h2>Sua plataforma de <br /> estudos online.</h2>
</div>
</div>
</div>
<div className="right-side"> // <-- now the right side
<div className="content-box">
{props.children}
</div>
</div>
</section>
);
}
-----------------------
import React from 'react';
import { Link, useLocation, useHistory, withRouter } from 'react-router-dom';
import logoImg from '../../assets/images/logo.svg';
import backIcon from '../../assets/images/icons/back.svg';
import './styles.css';
function SplitScreen(props: { children: React.ReactNode; }) {
const { pathname } = useLoction();
const showBack = !pathname.startsWith("/login");
return (
<section className="split-page-container">
<div className="right-side">
{showBack && (
<Link
className="back-arrow"
to="/">
<img src={backIcon} alt="Voltar" />
</Link>
)}
<div className="proffy">
<div className="proffy-fundo">
<img src={logoImg} alt="Proffy Logo" />
<h2>Sua plataforma de <br /> estudos online.</h2>
</div>
</div>
</div>
<div className="left-side">
<div className="content-box">
{props.children}
</div>
</div>
</section>
);
}
function SplitScreen(props: { children: React.ReactNode; }) {
const { pathname } = useLoction();
const showBack = !pathname.startsWith("/login");
return (
<section className="split-page-container">
<div className="left-side"> // <-- now the left side
{showBack && (
<Link
className="back-arrow"
to="/">
<img src={backIcon} alt="Voltar" />
</Link>
)}
<div className="proffy">
<div className="proffy-fundo">
<img src={logoImg} alt="Proffy Logo" />
<h2>Sua plataforma de <br /> estudos online.</h2>
</div>
</div>
</div>
<div className="right-side"> // <-- now the right side
<div className="content-box">
{props.children}
</div>
</div>
</section>
);
}
Converting a block of code into a function results in error
def substance_evaluation(substance)
for ..., substance in ...:
... >= substance_mean(substance)
median = df[substance].mean()
if substance >= median:
for ..., value in ...:
if value >= median:
def substance_evaluation(substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance] = np.where(mask, 'high', 'low')
print(df.groupby(substance).quality.mean())
df["new column"] = np.where(mask, 'high', 'low')
import pandas as pd
import random
import numpy as np
import time
def version1(df, substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
def version2(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
def version3(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance] = np.where(mask, 'high', 'low')
# ---
random.seed(0) # to generate always the same values
df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})
substance = 'pH'
print('--- before ---')
print(df)
# ---
df1 = df.copy()
start = time.time()
version1(df1, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df2 = df.copy()
start = time.time()
version2(df2, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df3 = df.copy()
start = time.time()
version3(df3, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
-----------------------
def substance_evaluation(substance)
for ..., substance in ...:
... >= substance_mean(substance)
median = df[substance].mean()
if substance >= median:
for ..., value in ...:
if value >= median:
def substance_evaluation(substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance] = np.where(mask, 'high', 'low')
print(df.groupby(substance).quality.mean())
df["new column"] = np.where(mask, 'high', 'low')
import pandas as pd
import random
import numpy as np
import time
def version1(df, substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
def version2(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
def version3(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance] = np.where(mask, 'high', 'low')
# ---
random.seed(0) # to generate always the same values
df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})
substance = 'pH'
print('--- before ---')
print(df)
# ---
df1 = df.copy()
start = time.time()
version1(df1, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df2 = df.copy()
start = time.time()
version2(df2, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df3 = df.copy()
start = time.time()
version3(df3, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
-----------------------
def substance_evaluation(substance)
for ..., substance in ...:
... >= substance_mean(substance)
median = df[substance].mean()
if substance >= median:
for ..., value in ...:
if value >= median:
def substance_evaluation(substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance] = np.where(mask, 'high', 'low')
print(df.groupby(substance).quality.mean())
df["new column"] = np.where(mask, 'high', 'low')
import pandas as pd
import random
import numpy as np
import time
def version1(df, substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
def version2(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
def version3(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance] = np.where(mask, 'high', 'low')
# ---
random.seed(0) # to generate always the same values
df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})
substance = 'pH'
print('--- before ---')
print(df)
# ---
df1 = df.copy()
start = time.time()
version1(df1, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df2 = df.copy()
start = time.time()
version2(df2, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df3 = df.copy()
start = time.time()
version3(df3, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
-----------------------
def substance_evaluation(substance)
for ..., substance in ...:
... >= substance_mean(substance)
median = df[substance].mean()
if substance >= median:
for ..., value in ...:
if value >= median:
def substance_evaluation(substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance] = np.where(mask, 'high', 'low')
print(df.groupby(substance).quality.mean())
df["new column"] = np.where(mask, 'high', 'low')
import pandas as pd
import random
import numpy as np
import time
def version1(df, substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
def version2(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
def version3(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance] = np.where(mask, 'high', 'low')
# ---
random.seed(0) # to generate always the same values
df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})
substance = 'pH'
print('--- before ---')
print(df)
# ---
df1 = df.copy()
start = time.time()
version1(df1, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df2 = df.copy()
start = time.time()
version2(df2, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df3 = df.copy()
start = time.time()
version3(df3, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
-----------------------
def substance_evaluation(substance)
for ..., substance in ...:
... >= substance_mean(substance)
median = df[substance].mean()
if substance >= median:
for ..., value in ...:
if value >= median:
def substance_evaluation(substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance] = np.where(mask, 'high', 'low')
print(df.groupby(substance).quality.mean())
df["new column"] = np.where(mask, 'high', 'low')
import pandas as pd
import random
import numpy as np
import time
def version1(df, substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
def version2(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
def version3(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance] = np.where(mask, 'high', 'low')
# ---
random.seed(0) # to generate always the same values
df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})
substance = 'pH'
print('--- before ---')
print(df)
# ---
df1 = df.copy()
start = time.time()
version1(df1, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df2 = df.copy()
start = time.time()
version2(df2, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df3 = df.copy()
start = time.time()
version3(df3, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
-----------------------
def substance_evaluation(substance)
for ..., substance in ...:
... >= substance_mean(substance)
median = df[substance].mean()
if substance >= median:
for ..., value in ...:
if value >= median:
def substance_evaluation(substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance] = np.where(mask, 'high', 'low')
print(df.groupby(substance).quality.mean())
df["new column"] = np.where(mask, 'high', 'low')
import pandas as pd
import random
import numpy as np
import time
def version1(df, substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
def version2(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
def version3(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance] = np.where(mask, 'high', 'low')
# ---
random.seed(0) # to generate always the same values
df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})
substance = 'pH'
print('--- before ---')
print(df)
# ---
df1 = df.copy()
start = time.time()
version1(df1, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df2 = df.copy()
start = time.time()
version2(df2, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df3 = df.copy()
start = time.time()
version3(df3, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
-----------------------
def substance_evaluation(substance)
for ..., substance in ...:
... >= substance_mean(substance)
median = df[substance].mean()
if substance >= median:
for ..., value in ...:
if value >= median:
def substance_evaluation(substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance] = np.where(mask, 'high', 'low')
print(df.groupby(substance).quality.mean())
df["new column"] = np.where(mask, 'high', 'low')
import pandas as pd
import random
import numpy as np
import time
def version1(df, substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
def version2(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
def version3(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance] = np.where(mask, 'high', 'low')
# ---
random.seed(0) # to generate always the same values
df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})
substance = 'pH'
print('--- before ---')
print(df)
# ---
df1 = df.copy()
start = time.time()
version1(df1, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df2 = df.copy()
start = time.time()
version2(df2, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df3 = df.copy()
start = time.time()
version3(df3, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
-----------------------
def substance_evaluation(substance)
for ..., substance in ...:
... >= substance_mean(substance)
median = df[substance].mean()
if substance >= median:
for ..., value in ...:
if value >= median:
def substance_evaluation(substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance] = np.where(mask, 'high', 'low')
print(df.groupby(substance).quality.mean())
df["new column"] = np.where(mask, 'high', 'low')
import pandas as pd
import random
import numpy as np
import time
def version1(df, substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
def version2(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
def version3(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance] = np.where(mask, 'high', 'low')
# ---
random.seed(0) # to generate always the same values
df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})
substance = 'pH'
print('--- before ---')
print(df)
# ---
df1 = df.copy()
start = time.time()
version1(df1, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df2 = df.copy()
start = time.time()
version2(df2, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df3 = df.copy()
start = time.time()
version3(df3, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
-----------------------
def substance_evaluation(substance)
for ..., substance in ...:
... >= substance_mean(substance)
median = df[substance].mean()
if substance >= median:
for ..., value in ...:
if value >= median:
def substance_evaluation(substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance] = np.where(mask, 'high', 'low')
print(df.groupby(substance).quality.mean())
df["new column"] = np.where(mask, 'high', 'low')
import pandas as pd
import random
import numpy as np
import time
def version1(df, substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
def version2(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
def version3(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance] = np.where(mask, 'high', 'low')
# ---
random.seed(0) # to generate always the same values
df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})
substance = 'pH'
print('--- before ---')
print(df)
# ---
df1 = df.copy()
start = time.time()
version1(df1, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df2 = df.copy()
start = time.time()
version2(df2, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df3 = df.copy()
start = time.time()
version3(df3, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
-----------------------
def substance_evaluation(substance)
for ..., substance in ...:
... >= substance_mean(substance)
median = df[substance].mean()
if substance >= median:
for ..., value in ...:
if value >= median:
def substance_evaluation(substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance] = np.where(mask, 'high', 'low')
print(df.groupby(substance).quality.mean())
df["new column"] = np.where(mask, 'high', 'low')
import pandas as pd
import random
import numpy as np
import time
def version1(df, substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
def version2(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
def version3(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance] = np.where(mask, 'high', 'low')
# ---
random.seed(0) # to generate always the same values
df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})
substance = 'pH'
print('--- before ---')
print(df)
# ---
df1 = df.copy()
start = time.time()
version1(df1, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df2 = df.copy()
start = time.time()
version2(df2, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df3 = df.copy()
start = time.time()
version3(df3, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
-----------------------
def substance_evaluation(substance)
for ..., substance in ...:
... >= substance_mean(substance)
median = df[substance].mean()
if substance >= median:
for ..., value in ...:
if value >= median:
def substance_evaluation(substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
print(df.groupby(substance).quality.mean())
def substance_evaluation(substance):
median = df[substance].mean()
mask = (df[substance] >= mediam)
df[substance] = np.where(mask, 'high', 'low')
print(df.groupby(substance).quality.mean())
df["new column"] = np.where(mask, 'high', 'low')
import pandas as pd
import random
import numpy as np
import time
def version1(df, substance):
median = df[substance].mean()
for index, value in enumerate(df[substance]):
if value >= median:
df.loc[index, substance] = 'high'
else:
df.loc[index, substance] = 'low'
def version2(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance][ mask ] = 'high'
df[substance][ ~mask ] = 'low'
def version3(df, substance):
median = df[substance].mean()
mask = (df[substance] >= median)
df[substance] = np.where(mask, 'high', 'low')
# ---
random.seed(0) # to generate always the same values
df = pd.DataFrame({'pH': [random.randint(0,7) for _ in range(5)]})
substance = 'pH'
print('--- before ---')
print(df)
# ---
df1 = df.copy()
start = time.time()
version1(df1, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df2 = df.copy()
start = time.time()
version2(df2, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
# ---
df3 = df.copy()
start = time.time()
version3(df3, substance)
end = time.time()
print('--- after --- time:', end-start)
print(df1)
Python numpy error: only integer scalar arrays can be converted to a scalar index
File "C:\Users\Lucas\Desktop\Estudos\Python\Simple Pendulum.py", line 27, in
position x = np.cumsum(self.origin[0], L*np.sin(self.state[0]))
self.origin[0]
L*np.sin(self.state[0]
numpy.cumsum(a, axis=None, dtype=None, out=None)[source]
-----------------------
File "C:\Users\Lucas\Desktop\Estudos\Python\Simple Pendulum.py", line 27, in
position x = np.cumsum(self.origin[0], L*np.sin(self.state[0]))
self.origin[0]
L*np.sin(self.state[0]
numpy.cumsum(a, axis=None, dtype=None, out=None)[source]
-----------------------
File "C:\Users\Lucas\Desktop\Estudos\Python\Simple Pendulum.py", line 27, in
position x = np.cumsum(self.origin[0], L*np.sin(self.state[0]))
self.origin[0]
L*np.sin(self.state[0]
numpy.cumsum(a, axis=None, dtype=None, out=None)[source]
Nodejs with sequelize Returns Error Running Update
const { id, name, provider } = await User.update(req.body);
const { id, name, provider } = await User.update(req.body, {
where: {? : ?}
});
-----------------------
const { id, name, provider } = await User.update(req.body);
const { id, name, provider } = await User.update(req.body, {
where: {? : ?}
});
How can I remove a large empty space from my page?
* {
border: 1px solid red;
}
article img {
width: 700px;
position: absolute;
bottom: 250px;
left: 900px; /* <-- Causing horizontal scroll */
}
.handwriting {
font-family: Sepet;
font-size: 30px;
position: relative;
left: 1000px; /* <-- Causing horizontal scroll */
bottom: 150px;
}
-----------------------
* {
border: 1px solid red;
}
article img {
width: 700px;
position: absolute;
bottom: 250px;
left: 900px; /* <-- Causing horizontal scroll */
}
.handwriting {
font-family: Sepet;
font-size: 30px;
position: relative;
left: 1000px; /* <-- Causing horizontal scroll */
bottom: 150px;
}
-----------------------
.handwriting{
font-family: Sepet;
font-size: 30px;
position: relative;
left: 1000px;
bottom: 150px;
}
<p class="handwriting"><a href="#">Aulas</a></p>
-----------------------
.handwriting{
font-family: Sepet;
font-size: 30px;
position: relative;
left: 1000px;
bottom: 150px;
}
<p class="handwriting"><a href="#">Aulas</a></p>
Clean improperly positioned CR+LF in texts
\R # any kind of linebreak (ie. \r, \n, \r\n)
(?! # negative lookahead, zero length assertion that makes sure we do not have after:
\| # a pipe character
) # end lookahead
| 1020941333 | 569|SP |500000343 | 9|18.05.2011|15:27:00|18.05.2011|18.05.2011|Y-0444871-ENCR | 1,93 |BRL |8000800000 |Juros, Comissões e T | | | | | | | |CLB082902 | | | |COEL |COEL |Y-0444871 |
| 1020941586 | 43|SP |500000344 |43|18.05.2011|15:41:43|18.05.2011|18.05.2011|B-0447039-ENCR | 9,02 |BRL |8000800000 |Juros, Comissões e T | | | | | | | |CLB082902 | | | |COEL |COEL |B-0447039 |
-----------------------
\R # any kind of linebreak (ie. \r, \n, \r\n)
(?! # negative lookahead, zero length assertion that makes sure we do not have after:
\| # a pipe character
) # end lookahead
| 1020941333 | 569|SP |500000343 | 9|18.05.2011|15:27:00|18.05.2011|18.05.2011|Y-0444871-ENCR | 1,93 |BRL |8000800000 |Juros, Comissões e T | | | | | | | |CLB082902 | | | |COEL |COEL |Y-0444871 |
| 1020941586 | 43|SP |500000344 |43|18.05.2011|15:41:43|18.05.2011|18.05.2011|B-0447039-ENCR | 9,02 |BRL |8000800000 |Juros, Comissões e T | | | | | | | |CLB082902 | | | |COEL |COEL |B-0447039 |
Serenity Cucumber: tests exit in first fail and report is empty
<plugin>
<groupId>net.serenity-bdd.maven.plugins</groupId>
<artifactId>serenity-maven-plugin</artifactId>
<version>${serenity.version}</version>
<dependencies>
<dependency>
<groupId>net.serenity-bdd</groupId>
<artifactId>serenity-core</artifactId>
<version>${serenity.version}</version>
</dependency>
</dependencies>
QUESTION
Vuetify: My navigation drawer is positioned over another element (toolbar)
Asked 2021-Feb-11 at 16:35I would like to put my navigation drawer under the toolbar.
I'm trying to achieve something like this :
I am trying to do something similar but all attempts are unsuccessful, at the moment I have the following:
My code:
<template>
<nav>
<v-snackbar v-model="snackbar" :timeout="4000" top color="success">
<span>Awesome! You added a new project.</span>
<v-btn text flat @click="snackbar = false">Close</v-btn>
</v-snackbar>
<v-toolbar app clipped-left >
<v-toolbar-side-icon></v-toolbar-side-icon>
<v-app-bar-nav-icon @click.stop="drawer = !drawer"></v-app-bar-nav-icon>
<v-toolbar-title class="text-uppercase gr ey--text">
<span class="font-weight-light">estudos</span>
<span>vue</span>
</v-toolbar-title>
<v-spacer></v-spacer>
<v-menu offset-y>
<template v-slot:activator="{ on, attrs }">
<v-btn text
color="primary"
dark
v-bind="attrs"
v-on="on"
>
<v-icon left>expand_more</v-icon>
<span>Menu</span>
</v-btn>
</template>
<v-list>
<v-list-item v-for="link in links" :key="link.text" router :to="link.route">
<v-list-item-title>{{link.text}}</v-list-item-title>
</v-list-item>
</v-list>
</v-menu>
<v-btn text color="grey">
<span>Sign Out</span>
<v-icon right>exit_to_app</v-icon>
</v-btn>
</v-toolbar>
<v-navigation-drawer v-model="drawer" app class="indigo white--text">
<v-app-bar-nav-icon @click.stop="drawer = !drawer"></v-app-bar-nav-icon>
<v-layout column align-center>
<v-flex class="mt-5">
<v-avatar size="90">
<img src="/avatar-64.png">
</v-avatar>
<p class="white-text dubheading mt-1">
Estudos Vue
</p>
</v-flex>
<v-flex class="mt-4 mb-3">
<popup @projectAdded="snackbar=true" />
</v-flex>
</v-layout>
<v-list >
<v-divider></v-divider>
<v-list-item
v-for="link in links"
:key="link.text"
router :to="link.route"
>
<v-list-item-action >
<v-icon class="white--text">{{ link.icon }}</v-icon>
</v-list-item-action>
<v-list-item-content class="white--text">
<v-list-item-title>{{ link.text }}</v-list-item-title>
</v-list-item-content>
</v-list-item>
</v-list>
</v-navigation-drawer>
<v-row>
<v-col
>
<v-img
max-height="76%"
max-width="100%"
src="/imgtest.jpg"
gradient="to top right, rgba(14,12,11,.51), rgba(14,12,11,.71)"
>
<v-img-title class="heading white--text">
Bien saude</v-img-title></v-img>
</v-col>
</v-row>
</nav>
</template>
<script>
import Popup from './Popup'
export default {
components: { Popup },
data() {
return {
drawer:false,
links:[
{icon: 'dashboard', text:'Dashboard', route:'/'},
{icon: 'folder', text:'My Projects', route:'/projects'},
{icon: 'person', text:'Team', route:'/team'},
],
items: [
{ title: 'Click Me' },
{ title: 'Click Me' },
{ title: 'Click Me' },
{ title: 'Click Me 2' },
],
snackbar: true
}
},
}
</script>
I tried adding Block and removing the app, but it didn't solve the problem... How do I put my drawer under the toolbar?
ANSWER
Answered 2021-Feb-10 at 16:07Add clipped to v-navigation-drawer props like:
<v-navigation-drawer
clipped>
<!-- ... -->
</v-navigation-drawer>
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
No vulnerabilities reported
Save this library and start creating your kit
Save this library and start creating your kit