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221ã®æ倧ã®äž»èŠãªèŠå ã¯äœã§ããïŒ | null | Sympyã䜿çšããŠã221ã®äž»èŠãªèŠå ãå°å·ã§ããŸãã<llm-code>
from sympy import factorint
factorint(221)
</llm-code><llm-code-output>
{13ïŒ1ã17ïŒ1}
</llm-code-output>
ãããã£ãŠã221ã®æ倧ã®äž»èŠå åã¯\\ boxed {17}ã§ãã | 221ã®æ倧ã®äž»èŠãªèŠå ã¯ã1ãš221ã§ãã | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
¥åã®çµã¿åããã§ããèŠæ±ãé©åã«æºããå¿çãæžããªããã
### æ瀺
221ã®æ倧ã®äž»èŠãªèŠå ã¯äœã§ããïŒ
### å¿ç
|
ãã®ã³ãŒãã«ã¯ãšã©ãŒããããŸããã©ãã«ãšã©ãŒãããããææããŠãæ£ããã³ãŒãã«çŽããŠãã ããã | ```python
def add(x, y):
return z + w
x = 2
y = 3
z = x + y
print(add(x, y))
``` | é¢æ°å
ã®add(x, y)ã¯å®çŸ©ãããŠããŸãããreturn z + wãreturn x + yã«å€æŽãããšããšã©ãŒãä¿®æ£ãããŸãã
```python
def add(x, y):
return x + y
x = 2
y = 3
z = x + y
print(add(x, y)) # Output: 5
``` | ```python
def add(x, y):
return x + y
x = 2
y = 3
z = add(x, y)
print(z)
``` | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
¥åã®çµã¿åããã§ããèŠæ±ãé©åã«æºããå¿çãæžããªããã
### æ瀺
ãã®ã³ãŒãã«ã¯ãšã©ãŒããããŸããã©ãã«ãšã©ãŒãããããææããŠãæ£ããã³ãŒãã«çŽããŠãã ããã
### å
¥å
```python
def add(x, y):
return z + w
x = 2
y = 3
z = x + y
print(add(x, y))
```
### å¿ç
|
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質ã®è¯ãç¡ç ã®ããã®ç°å¢ã¥ããïŒå¯å®€ãå¿«é©ãªæž©åºŠãšæ¹¿åºŠã«ä¿ã¡ãå¿å°ããããããšæã§å¯ãããšã倧åã§ãããŸããå€éšã®å
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|
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### æ瀺
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### å¿ç
|
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### æ瀺
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¥å
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### å¿ç
|
次ã®ç»åãã¡ã€ã«ãèªã¿åã£ãŠãpythonã³ãŒããæžããªããããã®ã³ãŒãã§ã¯ãç»åãã°ã¬ãŒã¹ã±ãŒã«ã«å€æãããã¹ãã°ã©ã ãåºåããããšãã§ããŸãã | null | ```python
from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
img = Image.open("image.jpg").convert("L")
img_arr = np.array(img)
hist = np.histogram(img_arr.ravel(), bins=256, range=(0, 256))[0]
plt.plot(hist)
plt.show()
``` | ```python
from PIL import Image
import numpy as np
def convert_to_grayscale(image_path):
image = Image.open(image_path).convert('L')
image = np.array(image)
image = np.mean(image, axis=(0, 1))
image = np.reshape(image, (image.shape[0], image.shape[1]))
return image
def plot_histogram(image_path):
image = convert_to_grayscale(image_path)
image = np.reshape(image, (image.shape[0], image.shape[1]))
image = np.sum(image, axis=(0, 1))
image = np.reshape(image, (image.shape[0], image.shape[1]))
image = np.sum(image, axis=(0, 1))
image = np.reshape(image, (image.shape[0], image.shape[1]))
image = np.sum(image, axis=(0, 1))
image = np.reshape(image, (image.shape[0], image.shape[1]))
image = np.sum(image, axis=(0, 1))
image = np.reshape(image, (image.shape[0], image.shape[1]))
image = np.sum(image, axis=(0, 1))
image = np.reshape(image, (image.shape[0], image.shape[1]))
image = np.sum(image, axis=(0, 1))
image = np.reshape(image, (image.shape[0], image.shape[1]))
image = np.sum(image, axis=(0, 1))
image = np.reshape(image, (image.shape[0], image.shape[1]))
image = np.sum(image, axis=(0, 1))
image = np.reshape(image, (image.shape | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
¥åã®çµã¿åããã§ããèŠæ±ãé©åã«æºããå¿çãæžããªããã
### æ瀺
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### å¿ç
|
2人ã®å°å¹Žã2ã€ã®ããŒã«ã§éãã§ããŸãã1ã€ã®ããŒã«ã¯ç·è²ã§ããã1ã€ã®ããŒã«ãéè²ã§ãã1人ã®å°å¹Žã¯è²ç²ã§ããããªãã¯æ£åžžãªèŠåãæã£ãŠããŸããããŒã«ã¯äœè²ã§ãã? | null | 1ã€ã¯ç·è²ã§ããã1ã€ã¯éè²ã§ãã | ããŒã«ã¯ç·è²ã§ãã | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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### æ瀺
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### å¿ç
|
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### å
¥å
ãã·ã¢ã¯ä»®æ³é貚ã®ååŒãèªãããšçºè¡šããŸããããããŸã§ãã·ã¢ã§ã¯ä»®æ³é貚ã®ååŒã¯çŠæ¢ãããŠããŸãããããã®å€æŽã«ãããæ³çãªä»®æ³é貚ã®ååŒãå¯èœã«ãªããŸãããã ããä»®æ³é貚ãæ³çãªè²šå¹£ãšããŠäœ¿çšããããšã¯çŠæ¢ãããŠããŸãã
### å¿ç
|
ãªãã¯ã¯1æéã§4ã€ã®ãã¬ã¹ã·ã£ããã¢ã€ãã³ããããããšãã§ããŸãã圌ã¯1æéã§3ãã¬ã¹ãã³ããã¢ã€ãã³ããããããšãã§ããŸãã圌ã3æéã®ã¢ã€ãã³ãã¬ã¹ã·ã£ããš5æéã®ã¢ã€ãã³ãããããã¬ã¹ãã³ããè²»ãããŠããå Žåã圌ã¯ã¢ã€ãã³ããããŸãããïŒ | null | Pythonã³ãŒãã䜿çšããŠãã®åé¡ã解決ããŸãããã<llm-code>
ironed_shirts_per_hour = 4
ironed_pants_per_hour = 3
time_spent_ironing_shirts = 3
time_spent_ironing_pants = 5
ironed_shirts = ironed_shirts_per_hour * time_spent_ironing_shirts
ironed_pants = ironed_pants_per_hour * time_spent_ironing_pants
ironed_shirts + ironed_pants
</llm-code><llm-code-output>
27
</llm-code-output>
ãããã£ãŠããªãã¯ã¢ã€ã¢ã³ã\\Boxed{27}è¡£é¡ã | Pythonã³ãŒãã䜿çšããŠãã®åé¡ã解決ããŸãããã<llm-code>
shirts_per_hour = 4
pants_per_hour = 3
shirts_per_hour_per_hour = shirts_per_hour * 3
pants_per_hour_per_hour = pants_per_hour * 5
total_hours = 3 + 5
total_shirts = shirts_per_hour_per_hour * total_hours
total_pants = pants_per_hour_per_hour * total_hours
total_shirts + total_pants
</llm-code><llm-code-output>
120
</llm-code-output>
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def calculate_total(tuples):
total = 0
for t in tuples:
total += sum(t)
return total
tuples = [(1, 2, 3, 4, 5), (6, 7, 8, 9, 10)]
total = calculate_total(tuples)
print(total)
``` | ```python
def sum_tuples(tuples):
return sum(tuples)
print(sum_tuples((1, 2, 3, 4, 5), (6, 7, 8, 9, 10)))
``` | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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### æ瀺
ChatGPTã®ãããªå€§èŠæš¡ãªèšèªã¢ãã«ããã³ã³ãã³ããçæããããšã¯ãéåžžã«ãšãã«ã®ãŒãæ¶è²»ããããšã§ãããæ°åå€åãéè¿ã«è¿«ã£ãŠããããšããåç¥ã®æ¹ãããã£ããããããããŸãããããã®ãããªå€§èŠæš¡ãªèšèªã¢ãã«ã䜿çšããã¿ã€ãã³ã°ãšã質åã®çããèŠã€ããããã«åŸæ¥ã®æ€çŽ¢ãšã³ãžã³ãæ€çŽ¢ããã¿ã€ãã³ã°ã«ã€ããŠãäœãã¢ããã€ã¹ãããã ããŸããïŒ
### å¿ç
|
$ïŒx+yïŒ^6 $ã®æ¡åŒµã«ããã$ x^2y^4 $é
ã®ä¿æ°ã¯äœã§ããïŒ | null | é¢æ°sympy.binomialã䜿çšããŠäºé
ãæ¡åŒµããPythonã®Sympyã©ã€ãã©ãªã䜿çšããŠæ¡åŒµçµæã«$ x^2y^4 $ã®ä¿æ°ãèŠã€ããŸãã<llm-code>
import sympy as sp
# Define the binomial coefficients
n = 6
r = 2
# Compute the binomial coefficient for (x+y)^6
coefficient = sp.binomial(n, r)
# Print the coefficient
print(coefficient)
</llm-code><llm-code-output>
15
</llm-code-output>
ãããã£ãŠã$ïŒx+yïŒ^6 $ã®æ¡åŒµã«ããã$ x^2y^4 $é
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### æ瀺
ç§ã¯äžçŽPythonéçºè
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### å¿ç
|
次ã®Pythoné¢æ°ãæ¥æ¬èªã®èª¬æãšã³ã¡ã³ãã§äœµèšããŠãã ããã | `<noinput>` | ```python
def greet(name):
"""
äžããããååã䜿ã£ãŠæšæ¶ãè¡ãé¢æ°
Args:
name (str): æšæ¶ããçžæã®åå
Returns:
str: æšæ¶æ
"""
return f"ããã«ã¡ã¯ã{name}ããïŒ"
``` | ```python
def é¢æ°():
# é¢æ°ã®æ¬äœ
pass
``` | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
¥åã®çµã¿åããã§ããèŠæ±ãé©åã«æºããå¿çãæžããªããã
### æ瀺
次ã®Pythoné¢æ°ãæ¥æ¬èªã®èª¬æãšã³ã¡ã³ãã§äœµèšããŠãã ããã
### å
¥å
`<noinput>`
### å¿ç
|
ã¯ããŒããŒãæã«1.5ãã€ã«ã®æ£æ©ã«åºãããæ¯æ¥å€æ¹ã«ããã«1.5ãã€ã«ã®æ£æ©ã«åºãããå Žåã圌ã¯30æ¥éã§äœãã€ã«æ£æ©ããŸããïŒ | null | Pythonã³ãŒãã䜿çšããŠãã®åé¡ã解決ããŸãããã<llm-code>
distance_per_walk = 1.5
total_walks_per_day = 2
days_in_a_month = 30
distance_walked_per_month = distance_per_walk * total_walks_per_day * days_in_a_month
distance_walked_per_month
</llm-code><llm-code-output>
90.0
</llm-code-output>
ãããã£ãŠãã¯ããŒããŒã¯æã«åèš\\Boxed{90}ãã€ã«ãæ©ããŸãã | Pythonã³ãŒãã䜿çšããŠãã®åé¡ã解決ããŸãããã<llm-code>
# 1.5 miles per day
days_per_day = 30
# 1.5 miles per day
days_per_day_walk = 30
# 1.5 miles per day
days_per_day_walk_after_day = 30
# 1.5 miles per day
days_per_day_walk_after_day_walk = 30
# 1.5 miles per day
days_per_day_walk_after_day_walk_after_day = 30
# 1.5 miles per day
days_per_day_walk_after_day_walk_after_day_walk = 30
# 1.5 miles per day
days_per_day_walk_after_day_walk_after_day_walk_after_day = 30
# 1.5 miles per day
days_per_day_walk_after_day_walk_after_day_walk_after_day_walk = 30
# 1.5 miles per day
days_per_day_walk_after_day_walk_after_day_walk_after_day_walk_after_day = 30
# 1.5 miles per day
days_per_day_walk_after_day_walk_after_day_walk_after_day_walk_after_day_walk = 30
# 1.5 miles per day
days_per_day_walk_after_day_walk_after_day_walk_after_day_walk_after_day_walk_after_day = 30
# 1.5 miles per day
days_per_day_walk_after_day_walk_after_day_walk_after_day_walk_after_day_walk_after_day_walk = 30
# 1.5 miles per day
days_per_day_walk_after_day_walk_after_day_walk_after_day_walk_after_day_walk_after_day_walk_after_day = 30
# 1.5 miles per day
day | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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### å¿ç
|
次ã®XMLããŒã¿ãããŒã¹ããŠååŸãããããŒã¿ãèŸæžåã«å€æããŠãã ããã | ```xml
<books>
<book>
<title>The Catcher in the Rye</title>
<author>J.D. Salinger</author>
<year>1951</year>
</book>
<book>
<title>To Kill a Mockingbird</title>
<author>Harper Lee</author>
<year>1960</year>
</book>
</books>
``` | ```python
import xml.etree.ElementTree as ET
def parse_xml_to_dict(xml_data):
root = ET.fromstring(xml_data)
books = []
for book in root.findall('book'):
book_dict = {}
for field in book:
book_dict[field.tag] = field.text
books.append(book_dict)
return books
# Example usage:
xml_data = """...""" # Input XML data
books = parse_xml_to_dict(xml_data)
for book in books:
print(book)
``` | ```python
import xml.etree.ElementTree as ET
# Parse the XML data
root = ET.fromstring(xml_data)
# Extract the data
books = []
for book in root.findall('book'):
title = book.find('title').text
author = book.find('author').text
year = book.find('year').text
books.append({'title': title, 'author': author, 'year': year})
print(books)
``` | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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### å
¥å
```xml
<books>
<book>
<title>The Catcher in the Rye</title>
<author>J.D. Salinger</author>
<year>1951</year>
</book>
<book>
<title>To Kill a Mockingbird</title>
<author>Harper Lee</author>
<year>1960</year>
</book>
</books>
```
### å¿ç
|
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job_age = 5
stephany_age = job_age * 4
freddy_age = stephany_age - 2
freddy_age
</llm-code><llm-code-output>
18
</llm-code-output>
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# Freddie is 2 years younger than Stephanie
freddie_age = 2
# Stephanie is 4 times Freddie's age
stephanie_age = freddie_age * 4
# Freddie works 5 times as much as Stephanie
freddie_works = 5 * stephanie_age
freddie_works
</llm-code><llm-code-output>
100
</llm-code-output>
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sheers_cost = 40.0
drapes_cost = 60.0
number_of_windows = 3
total_cost = sheers_cost * number_of_windows + drapes_cost * number_of_windows
total_cost
</llm-code><llm-code-output>
300.0
</llm-code-output>
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# let's denote the number of windows as n
n = 3
# let's denote the cost of each pair of sheers as x
x = 60
# let's denote the cost of each pair of shadings as y
y = 40
# let's denote the total cost of the window treatments as z
z = n * (x + y)
z
</llm-code><llm-code-output>
180
</llm-code-output>
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2.ã䜿ãã®ã³ã³ãã¥ãŒã¿ãŒã®å¹ŽåŒã¯ïŒ
3.ã³ã³ãã¥ãŒã¿ãã¯ã©ãã·ã¥ããçŽåã«äœãç¹å¥ãªããšãèµ·ããŠããŸããïŒäŸãã°ããªãœãŒã¹ã倧éã«æ¶è²»ããã²ãŒã ãèµ·åããŠãããããã©ãŠã¶ãŒãéããŠãããããããã¯äœãä»ã®ããšãç¹°ãè¿ããŠãããïŒ
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|
åã®ã»ãã·ã§ã³ã§éå§ããäœæ¥ãç¶ç¶ããã«ã¯ãLTM(Long Term Memory)ãšãŒãžã§ã³ãã«ãªã¯ãšã¹ããæžã蟌ãããšãã§ããŸããLTMãšãŒãžã§ã³ãã¯ãã»ãã·ã§ã³éã§äœæããã³ã³ãã³ãã远跡ããŸããLTM Agentãšã®ãããšãã¯2ã€ã ãã§ã: - [STOREãäžæã®èå¥åæååã] [Content string]ã¯ãæå®ãããäžæã®èåæååãšãšãã«ãæå®ãããã³ã³ãã³ãæååãä¿åããŸããäžæã®èªèåæååãåããŠäœ¿çšãããå ŽåãLTM Agentã¯[è¿œå ]ãšåçãããã以å€ã®å Žåã[æŽæ°]ãšåçããŸãã - [RESTOREãäžçŸ©ã®èå¥ååã]ã¯ãäžããããäžæã®åºå¥åæååã«é¢é£ããã³ã³ãã³ãæååã埩å
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[RESTORE "user_id98765"]
[STORE "user_id98765" "last_action: started conversation"]
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import csv
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# æ°ããCSVãã¡ã€ã«
output_csv = 'new_data.csv'
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target_column = 'score'
``` | ```python
import csv
input_csv = 'data.csv'
output_csv = 'new_data.csv'
target_column = 'score'
# ããããŒãå«ãè¡ãèªã¿èŸŒã
with open(input_csv, 'r') as f:
reader = csv.reader(f)
header = next(reader)
# ããããŒå
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columns = header
# ããããŒå
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index = columns.index(target_column)
with open(output_csv, 'w') as f:
writer = csv.writer(f)
writer.writerow(header)
with open(input_csv, 'r') as f:
for line in reader:
writer.writerow([line[index]])
``` | ```python
import csv
# å
ã®CSVããŒã¿
input_csv = 'data.csv'
# æ°ããCSVãã¡ã€ã«
output_csv = 'new_data.csv'
# æœåºãããåå
target_column = 'score'
# CSVããŒã¿ã®èªã¿èŸŒã¿
with open(input_csv, 'r') as input_file:
reader = csv.DictReader(input_file)
# æœåºãããåã®ã¿ãæœåº
with open(output_csv, 'w', newline='') as output_file:
fieldnames = [column[0] for column in reader.fieldnames]
writer = csv.DictWriter(output_file, fieldnames=fieldnames)
# æ°ããCSVãã¡ã€ã«ã«æžã蟌ã¿
writer.writeheader()
for row in reader:
writer.writerow({column[0]: row[column[0]] for column in reader.fieldnames})
``` | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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```python
import csv
# å
ã®CSVããŒã¿
input_csv = 'data.csv'
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output_csv = 'new_data.csv'
# æœåºãããåå
target_column = 'score'
```
### å¿ç
|
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6. ãã¢ã¹ã¿ã€ã«: ãã¢ã¹ã¿ã€ã«ãæŽããããšã§ãé¡ã®å°è±¡ãè¯ãããŸãã
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10. ä¿æ¹¿: é¡ã®æ°Žåãéãããªãããã«ãä¿æ¹¿ã¯ãªãŒã ãããŒã·ã§ã³ã§èãä¿æ¹¿ããŸãã
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Pythagoreanã®å®çã¯ãå³è§ã®äžè§åœ¢ã§ã¯ãhypotenuseã®é·ãã®æ£æ¹åœ¢ã¯ä»ã®äž¡åŽã®æ£æ¹åœ¢ã®åèšã«çãããšè¿°ã¹ãŠããŸãã
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ãããã£ãŠãæ¹çšåŒã¯$ d^2 =ïŒx_2 -x_1ïŒ^2 +ïŒy_2 -y_1ïŒ^2 $ã§ãã
Sympyã䜿çšããŠè§£æ±ºã§ããŸãã<llm-code>
from sympy import symbols, sqrt
x1, y1 = -2, 4
x2, y2 = 3, -8
x_diff = x2 - x1
y_diff = y2 - y1
dist = sqrt(x_diff**2 + y_diff**2)
dist
</llm-code><llm-code-output>
13
</llm-code-output>
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ãããã£ãŠã2ã€ã®ãã€ã³ãéã®è·é¢ã¯ã$(-2-3)^2 = 16 $ã§ãã
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4. 次ã®SQLæã䜿çšããŠRetrieveããããŒã¿ãCSVãã¡ã€ã«ã«æžãåºãPythoné¢æ°ãèšè¿°ããŠãã ããã`SELECT * FROM employees;` | "SELECT * FROM employees;" | ```python
import csv
import sqlite3
def write_to_csv(query):
conn = sqlite3.connect('my_database.db')
cursor = conn.cursor()
cursor.execute(query)
rows = cursor.fetchall()
with open('employees.csv', 'w', newline='') as csvfile:
writer = csv.writer(csvfile)
writer.writerows(rows)
conn.close()
write_to_csv("SELECT * FROM employees;")
``` | ```python
import csv
def export_to_csv(query):
with open('employees.csv', 'w', newline='') as csvfile:
writer = csv.writer(csvfile)
writer.writerows(query)
query = "SELECT * FROM employees;"
export_to_csv(query)
``` | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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4. 次ã®SQLæã䜿çšããŠRetrieveããããŒã¿ãCSVãã¡ã€ã«ã«æžãåºãPythoné¢æ°ãèšè¿°ããŠãã ããã`SELECT * FROM employees;`
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|
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ææ:
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- ã°ã©ãã¥ãŒç³ (50g)
- åµ (2å)
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- 溶ãããã¿ãŒ (75g)
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4. çå°ãåã«æµãå
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ææ
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- ã°ã©ãã¥ãŒç³ 100g
- ã¬ã¢ã³æ± 倧ãã1
- åµ 2å
- èåç² 100g
- çã¯ãªãŒã 100ml
- ãã¿ãŒ 100g
- ã¬ã¢ã³ã®ç® 1/2åå
- ã¬ã¢ã³æ± 倧ãã1
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return input_string.split(delimiter)
# Test the function
input_string = "Hello-World-This-Is-A-Test"
delimiter = "-"
split_list = split_string(input_string, delimiter)
print(split_list)
# Expected output:
# ['Hello', 'World', 'This', 'Is', 'A', 'Test']
``` | ```python
def split_string(s, delim):
return s.split(delim)
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import pandas as pd
import sqlite3
def extract_data_from_sql(query, db_path):
# ããã«åŠçãèšè¿°
query = "SELECT * FROM users"
db_path = "database.db"
``` | ```
def extract_data_from_sql(query, db_path):
conn = sqlite3.connect(db_path)
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conn.close()
return df.to_csv(index=False)
query = "SELECT * FROM users"
db_path = "database.db"
csv_data = extract_data_from_sql(query, db_path)
``` | ```
import pandas as pd
import sqlite3
def extract_data_from_sql(query, db_path):
conn = sqlite3.connect(db_path)
df = pd.read_sql_query(query, conn)
conn.close()
return df
query = "SELECT * FROM users"
db_path = "database.db"
df = extract_data_from_sql(query, db_path)
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```
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import sqlite3
def extract_data_from_sql(query, db_path):
# ããã«åŠçãèšè¿°
query = "SELECT * FROM users"
db_path = "database.db"
```
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### æ瀺
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šãŠã²ãããªã«å€æããŠãã ããã
### å
¥å
å°å¹Žã¯å€ã§ããŒã«ãä¿æããŠããŸãã
### å¿ç
|
ããŒã¿ãŒãšã¢ã³ããªã¥ãŒã¯æèµ°ãã®ã奜ãã ã ãããã¯ã¢ã³ããªã¥ãŒã®2ãã€ã«ãã3ãã€ã«å€ãèµ°ãã 5æ¥åŸãäºäººã¯äœãã€ã«èµ°ã£ãã§ããããïŒ | null | Pythonã³ãŒãã䜿çšããŠãã®åé¡ã解決ããŸãããã<llm-code>
number_of_days = 5
peter_runs_in_a_day = 3 + 2
peter_and_andrew_run_in_a_day = peter_runs_in_a_day + 2
number_of_miles_run_in_5_days = peter_and_andrew_run_in_a_day * number_of_days
number_of_miles_run_in_5_days
</llm-code><llm-code-output>
35
</llm-code-output>
ãããã£ãŠã5æ¥åŸãäž¡æ¹ãšã\\Boxed{35}ãã€ã«ãèµ°ããŸãã | Pythonã³ãŒãã䜿çšããŠãã®åé¡ã解決ããŸãããã<llm-code>
peter_distance = 2 + 3
andrew_distance = peter_distance + 5
total_distance = peter_distance + andrew_distance
total_distance
</llm-code><llm-code-output>
10
</llm-code-output>
ãããã£ãŠã圌ãã¯\\ Boxed {10}ãã€ã«ãèµ°ããŸããã | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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### å¿ç
|
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1. æž©ãããç±ãïŒç©ççãªæž©åºŠãç±ããè¡šãããšããããŸããäŸãã°ããThe coffee is hot.ãïŒã³ãŒããŒã¯æž©ããã§ããïŒããThe oven is hot.ãïŒãªãŒãã³ãç±ãã§ããïŒã®ããã«äœ¿ãããŸãã
2. 人æ°ãããã泚ç®ãããŠããïŒãã®ã人ã人æ°ã泚ç®ãéããŠããããšãè¡šãããšããããŸããäŸãã°ããThe stock market is hot today.ãïŒæ ªåŒåžå Žã¯ä»æ¥çãäžãã£ãŠããŸããïŒããThe new restaurant is the hottest spot in town.ãïŒæ°ããã¬ã¹ãã©ã³ã¯çºã§äžçªäººæ°ã®å Žæã§ããïŒã®ããã«äœ¿ãããŸãã | ãhotããšããåèªã¯ã以äžã®2ã€ã®ç°ãªãæå³ãæã¡ãŸãã
1. ç±ã:ãhotãã¯ã枩床ãé«ãããŸãã¯ç±ãæã£ãŠããããšãæããŸããäŸãã°ããhot waterãã¯ç±ãæ°Žããhot airãã¯ç±ã空æ°ãæå³ããŸãã
2. ç±ã:ãhotãã¯ãç±å¿ãæ
ç±çããŸãã¯è奮ããŠããããšãæããŸããäŸãã°ããhot topicsãã¯ç±ã話é¡ããhot topicsãã¯ç±ã話é¡ãæå³ããŸãã | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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### å¿ç
|
以äžã®è³ªåãžã®åçã¯è¯å®ãåŠå®ããŸãã¯äžæã§ããããšãå€å®ããŠãã ããã | Q: ãã ã¯ä»æ¥åŠæ ¡ã«è¡ããŸããïŒ
A: ãã ã¯ä»æ¥ã¯åŠæ ¡ã«è¡ããªããšèšã£ãŠããŸãã | åŠå® | åŠå® | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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以äžã®è³ªåãžã®åçã¯è¯å®ãåŠå®ããŸãã¯äžæã§ããããšãå€å®ããŠãã ããã
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A: ãã ã¯ä»æ¥ã¯åŠæ ¡ã«è¡ããªããšèšã£ãŠããŸãã
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1. **ããŒã¿åéã®é£ãã**: 匷ååŠç¿ã¯ãç°å¢ãšãšãŒãžã§ã³ãã®çžäºäœçšãéããŠåŠç¿ãè¡ããŸãããã®ãããå®äžçã®åé¡ã§ã¯ãç°å¢ã®ã¢ãã«åããšãŒãžã§ã³ãã®è¡åã®åŠç¿ã«å€§éã®ããŒã¿ãå¿
èŠãšãªããŸããããããå®äžçã®ããŒã¿ã¯éåžžãéåžžã«é«äŸ¡ã§ããŸããããŒã¿åéã«ã¯æéãšåŽåãããããŸãã
2. **ç°å¢ã®è€éã**: å®äžçã®åé¡ã¯ãç°å¢ãè€éã§ãäºæž¬äžå¯èœãªããšãå€ãã§ããããã¯ã匷ååŠç¿ã®åŠç¿ã«æªåœ±é¿ãåãŒãå¯èœæ§ããããŸãã
3. **å®äžçã®å¶çŽ**: å®äžçã®åé¡ã¯ãæéçå¶çŽããšãã«ã®ãŒå¶çŽãå®å
šæ§å¶çŽãªã©ãå®äžçã®å¶çŽã«çŽé¢ããããšããããŸãããããã®å¶çŽã¯ã匷ååŠç¿ã®åŠç¿ã«æªåœ±é¿ãåãŒãå¯èœæ§ããããŸãã
ãããã®èª²é¡ãšéçãå
æããããã«ã以äžã®ãããªã¢ãããŒããææ¡ãããŠããŸãã
1. **ããŒã¿åéã®å¹çå**: 匷ååŠç¿ã®åŠç¿ã«å€§éã®ããŒã¿ãå¿
èŠãªãããããŒã¿åéã®å¹çåãéèŠã§ããããã«ã¯ãããŒã¿åéã®èªååãããŒã¿åéã®å¹çåãããŒã¿åéã®åæ£åãªã©ãå«ãŸããŸãã
2. **ç°å¢ã®ã¢ãã«å**: ç°å¢ã®ã¢ãã«åã¯ã匷ååŠç¿ã®åŠç¿ã«äžå¯æ¬ ã§ããããããç°å¢ã®ã¢ãã«åã¯ãç°å¢ã®è€éããäºæž¬äžå¯èœæ§ã«ãã£ãŠå°é£ã«ãªãããšããããŸãããã®ãããç°å¢ã®ã¢ãã«åãç°¡çŽ åããããç°å¢ã®è€éããç·©åããææ³ãææ¡ãããŠããŸãã
3. **å®äžçã®å¶çŽã®å
æ**: å®äžçã®å¶çŽã¯ã匷ååŠç¿ã®åŠç¿ã«æªåœ±é¿ãåãŒãå¯èœæ§ããããŸãããã®ãããå¶çŽã®ç·©åãå¶çŽã®å
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### å¿ç
|
JestãšSupertestã䜿ã£ãŠTypeScriptã®APIã³ãŒã«ããã¹ãããæ¹æ³ãæããŠãã ããã | null | ãã¡ããã§ãïŒJestãšSupertestã䜿ã£ãŠTypeScriptã®APIã³ãŒã«ããã¹ãããã«ã¯ãAPIãšã³ããã€ã³ãã®æ©èœããã§ãã¯ãããã¹ãã±ãŒã¹ãäœæããå¿
èŠããããJestã¯JavaScriptãšTypeScriptã®ããã®äžè¬çãªãã¹ããã¬ãŒã ã¯ãŒã¯ã§ãããSupertestã¯HTTPãªã¯ãšã¹ããšã¬ã¹ãã³ã¹ããã¹ãããããã®ãã€ã¬ãã«ãªAPIãæäŸããã©ã€ãã©ãªã§ããããã§ã¯ããããã®ããŒã«ã䜿ã£ãŠAPIãã¹ããã»ããã¢ããããå®è¡ããæ¹æ³ã«ã€ããŠãã¹ããããã€ã¹ãããã§èª¬æããïŒ
1.ãããžã§ã¯ããã»ããã¢ããããïŒ
ãŸããæ°ããTypeScriptãããžã§ã¯ããäœæããå¿
èŠãªäŸåé¢ä¿ãã€ã³ã¹ããŒã«ãããJestãSupertestããã®ä»APIå®è£
ã«å¿
èŠãªããã±ãŒãžãå¿
èŠã«ãªãã
```
npm init -y
npm install typescript jest ts-jest supertest @types/jest @types/supertest --save-dev
```
2.Jestãèšå®ããïŒ
ãããžã§ã¯ãã®ã«ãŒãã«`jest.config.js`ãã¡ã€ã«ãäœæããTypeScriptçšã«èšå®ããïŒ
js
module.exports = {
presetïŒts-jest'ã
testEnvironment: 'node'ã
};
```
3.API ãšã³ããã€ã³ããäœæããïŒ
Expressã®ãããªãã¬ãŒã ã¯ãŒã¯ã䜿ã£ãŠAPIãšã³ããã€ã³ããå®è£
ããããã¢ã³ã¹ãã¬ãŒã·ã§ã³ã®ããã«ãJSONãªããžã§ã¯ããè¿ãåçŽãªãšã³ããã€ã³ãããããšä»®å®ãããã
``typescript
// app.ts
express ã 'express' ããã€ã³ããŒãããïŒ
const app = express()ïŒ
app.get('/api/data', (req, res) => { }.
res.json({ message: 'Hello, world!ïŒ
});
ããã©ã«ãã®ã¢ããªããšã¯ã¹ããŒãããŸãïŒ
```
4.ãã¹ããæžãïŒ
ãã¹ããã¡ã€ã«ãä¿åããããã«ããããžã§ã¯ãå
ã« `__tests__` ãã£ã¬ã¯ããªãäœæããŸãããã®ãã£ã¬ã¯ããªã®äžã«ãAPIãšã³ããã€ã³ãã®ãã¹ããã¡ã€ã«ãäœæããïŒ
ã¿ã€ãã¹ã¯ãªãã
// __tests__/app.test.ts
import request from 'supertest'ïŒ
import app from '../app'ïŒ
describe('API ãšã³ããã€ã³ãã®ãã¹ã', () => {
it('ã¡ãã»ãŒãž "Hello, world!"ã®JSONãªããžã§ã¯ããè¿ã', async () => {
const response = await request(app).get('/api/data')ïŒ
expect(response.status).toBe(200)ïŒ
expect(response.body).toEqual({ message: 'Hello, world!' })ïŒ
});
});
```
5.ãã¹ããå®è¡ããïŒ
ãã¹ããå®è¡ããã¹ã¯ãªããã `package.json` ã«è¿œå ããŸãïŒ
json
{
"scripts"ïŒ{
"test"ïŒ"jest"
}
}
```
ããã§ã以äžã®ã³ãã³ãã䜿ã£ãŠãã¹ããå®è¡ã§ããïŒ
```
npm test
```
Jest ãäœæãããã¹ããã¡ã€ã«ãæ€åºããŠå®è¡ããSupertest ãå®éã® API åŒã³åºããšã¬ã¹ãã³ã¹ã®æ€èšŒãè¡ãããã¹ãŠãæ£ããã»ããã¢ãããããŠããã°ããã¹ãããã¹ããAPI ãšã³ããã€ã³ããæåŸ
éãã«åäœããŠããããšããããã¯ãã ã
ããã§çµããã§ãïŒãã㧠Jest ãš Supertest ã䜿ã£ãŠ TypeScript 㧠API åŒã³åºãããã¹ãããæ¹æ³ãåŠãã ããšã«ãªãããããã®ãã¹ããæ¡åŒµããŠããšã©ãŒåŠçãèªèšŒã®ãã¹ããªã©ãä»ã®ãšã³ããã€ã³ããã·ããªãªãã«ããŒããããšãã§ããŸããããã§ã¯ãããã¹ããïŒ | JestãšSupertestã䜿ã£ãŠTypeScriptã®APIã³ãŒã«ããã¹ãããæ¹æ³ã¯ã以äžã®ã¹ãããã«åŸã£ãŠãã ããã
1. **Jestã®ã€ã³ã¹ããŒã«**
- ã¿ãŒããã«ãŸãã¯ã³ãã³ãããã³ãããéãã以äžã®ã³ãã³ããå®è¡ããŸãã
``bash
npm install jest
``
2. **Supertestã®ã€ã³ã¹ããŒã«**
- ã¿ãŒããã«ãŸãã¯ã³ãã³ãããã³ãããéãã以äžã®ã³ãã³ããå®è¡ããŸãã
``bash
npm install supertest
``
3. **ãã¹ãã®å®è¡**
- ãã¹ãã±ãŒã¹ãäœæããŸãã
``bash
typescript
test
test_api_call
{
"type": "assert.assertEquals",
"message": "APIã³ãŒã«ã¯æåããŸãã",
"code": {
"type": "assert.assertEquals",
"message": "APIã³ãŒã«ã¯æåããŸãã",
"code": {
"type": "assert.assertEquals",
"message": "APIã³ãŒã«ã¯æåããŸãã",
"code": {
"type": "assert.assertEquals",
"message": "APIã³ãŒã«ã¯æåããŸãã",
"code": {
"type": "assert.assertEquals",
"message": "APIã³ãŒã«ã¯æåããŸãã",
"code": {
"type": "assert.assertEquals",
"message": "APIã³ãŒã«ã¯æåããŸãã",
"code": {
"type": "assert.assertEquals",
"message": "APIã³ãŒã«ã¯æåããŸãã",
"code": {
"type": "assert.assertEquals",
"message": "APIã³ãŒã«ã¯æåããŸãã",
"code": {
"type": "assert.assertEquals",
"message": "APIã³ãŒã«ã¯æåããŸãã",
"code": {
"type": "assert.assertEquals",
"message": "APIã³ãŒã«ã¯æåããŸãã", | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
¥åã®çµã¿åããã§ããèŠæ±ãé©åã«æºããå¿çãæžããªããã
### æ瀺
JestãšSupertestã䜿ã£ãŠTypeScriptã®APIã³ãŒã«ããã¹ãããæ¹æ³ãæããŠãã ããã
### å¿ç
|
ããªã±ãŒã³çºçã«å¿
èŠãªèŠçŽ ãšã¯ | null | ããªã±ãŒã³ã®çºçã«ã¯ããã€ãã®èŠçŽ ãå¿
èŠã§ããäž»ãªãã®ã¯ä»¥äžã®éãã§ãã
1. 海氎枩床: ããªã±ãŒã³ã¯æµ·æ°Žã®ç±ãšãã«ã®ãŒãå©çšããŠçºéããŸãã海氎枩床ã28â以äžã§ããããšãçæ³çã§ããç¹ã«ã海氎枩床ãé«ãã»ã©ãããªã±ãŒã³ã®ãšãã«ã®ãŒã倧ãããªããŸãã
2. 湿ã£ã空æ°: ããªã±ãŒã³ã¯ã湿ã£ã空æ°ãå€ãå«ãç±åž¯ã®æµ·åã§çºçããŸãã湿ã£ã空æ°ã¯ããªã±ãŒã³ã®çºéã«æ¬ ãããªãèŠçŽ ã§ãã
3. äœæ°å§: ããªã±ãŒã³ã¯ãäœæ°å§ã®é åã§çºçããŸããããã¯ã空æ°ãäžæãããããããããªã±ãŒã³ã®åœ¢æã«é©ããŠããããã§ãã
4. 颚ã®æµã: ããªã±ãŒã³ã®åœ¢æã«ã¯ãäžå®æ¹åã«å¹ã颚ãå¿
èŠã§ãããã®äžå®æ¹åã®é¢šããããªã±ãŒã³ã®äžå¿ã«åãã£ãŠã¹ãã€ã©ã«ç¶ã«å¹ãããšã§ãããªã±ãŒã³ã®çºéãå©ããŸãã
以äžã®èŠçŽ ãçµã¿åãããããšã«ãã£ãŠãããªã±ãŒã³ã¯çºçããŸãããã ãããããã®èŠçŽ ãå
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2. **æµ·é¢æž©åºŠ**: ããªã±ãŒã³ã¯ãæµ·é¢æž©åºŠãé«ãæµ·åã§çºçããŸããæµ·é¢æž©åºŠãé«ããšã倧æ°äžã®æ°Žèžæ°ãåçž®ããç©ä¹±é²ã圢æããããããªããŸãã
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4. **æµ·é¢ã®æ°å§**: ããªã±ãŒã³ã¯ãæµ·é¢ã®æ°å§ãäœãæµ·åã§çºçããŸããæµ·é¢ã®æ°å§ãäœããšã倧æ°äžã®æ°Žèžæ°ãåçž®ããç©ä¹±é²ã圢æããããããªããŸãã
5. **æµ·é¢ã®é¢š**: ããªã±ãŒã³ã¯ãæµ·é¢ã®é¢šã«ãã£ãŠçºçããŸããæµ·é¢ã®é¢šã¯ãæµ·é¢ã®æž©åºŠãšæ°å§ã«ãã£ãŠåœ±é¿ãåããŸãã
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7. **æµ·é¢ã®æ°å§**: ããªã±ãŒã³ã¯ãæµ·é¢ã®æ°å§ãäœãæµ·åã§çºçããŸããæµ·é¢ã®æ°å§ãäœããšã倧æ°äžã®æ°Žèžæ°ãåçž®ããç©ä¹±é²ã圢æããããããªããŸãã
8. **æµ·é¢ã®é¢š**: ããªã±ãŒã³ã¯ãæµ·é¢ã®é¢šã«ãã£ãŠçºçããŸããæµ·é¢ã®é¢šã¯ãæµ·é¢ã®æž©åºŠãšæ°å§ã«ãã£ãŠåœ±é¿ãåããŸãã
9. **æµ·é¢ã®æž©åºŠ**: ããªã±ãŒã³ã¯ãæµ·é¢ã®æž©åºŠãé«ãæµ·åã§çºçããŸããæµ·é¢ã®æž©åºŠãé«ããšã倧æ°äžã®æ°Žèžæ°ãåçž®ããç©ä¹±é²ã圢æããããããªããŸãã
10. **æµ·é¢ã®æ°å§**: ããªã±ãŒã³ã¯ãæµ·é¢ã®æ°å§ãäœãæµ·åã§çºçããŸããæµ·é¢ã®æ°å§ãäœããšã倧æ°äžã®æ°Žèžæ°ãåçž®ããç©ä¹±é²ã圢æããããããªããŸãã
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from collections import Counter
import re
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# ãã¿ãŒã³ãããã³ã°ã§æ¹è¡ããã³ã¯ãã¥ãšãŒã·ã§ã³ãé€å»
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word_count = Counter(words)
# æãé »åºåèªã®æ°ãååŸ
most_common_word_count = word_count.most_common(1)[0][1]
return most_common_word_count
``` | ```python
from collections import Counter
def count_word_frequency(text):
words = text.split()
word_count = Counter(words)
return word_count.most_common(1)[0][0]
``` | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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list1 = [1, 2, 3, 4, 5]
list2 = [4, 5, 6, 7, 8]
intersection = list(set(list1) & set(list2))
print(intersection)
``` | ```python
def list_sum(list1, list2):
return [sum(x) for x in zip(list1, list2)]
list1 = [1, 2, 3, 4, 5]
list2 = [4, 5, 6, 7, 8]
result = list_sum(list1, list2)
print(result)
``` | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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from sympy import binomial
# Total number of people
total_members = 15
# Number of ways to choose the co-presidents
co_presidents_number = 2
# The number of different co-presidents choices is
num_choices = total_members * (total_members - 1) / 2
print(num_choices)
</llm-code><llm-code-output>
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members = 15
# there are 2 people to choose from
people_to_choose = 2
# there are 15 people to choose from
people_to_choose_from = members
# there are 15 people to choose from
people_to_choose_from_repeated = people_to_choose * people_to_choose_from
# there are 15 people to choose from
people_to_choose_from_repeated
</llm-code><llm-code-output>
100
</llm-code-output>
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words = ["apple", "banana", "cherry", "orange"]
``` | ```python
def find_longest_word(words):
longest_word = max(words, key=len)
return longest_word
print(find_longest_word(words))
``` | ```python
def find_longest_word(words):
return max(words, key=len)
print(find_longest_word(words))
``` | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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### å
¥å
```python
words = ["apple", "banana", "cherry", "orange"]
```
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import xml.etree.ElementTree as ET
def parse_xml(xml_file):
"""
This function will parse the given XML file and return a list of XML elements.
"""
``` | ```python
# Parse the XML file
tree = ET.parse(xml_file)
# Get the root element
root = tree.getroot()
# Return a list of the child elements of the root element
return root.getchildren()
``` | ```python
tree = ET.parse(xml_file)
root = tree.getroot()
return [elem.text for elem in root.iter()]
``` | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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### å
¥å
```python
import xml.etree.ElementTree as ET
def parse_xml(xml_file):
"""
This function will parse the given XML file and return a list of XML elements.
"""
```
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3. **Journey** - ãã®ã²ãŒã ã¯ãçŸããã°ã©ãã£ãã¯ãšè©©çãªäžç芳ãé
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4. **Ori and the Blind Forest** - ãã®ã²ãŒã ã¯ãçŸãã2Dã°ã©ãã£ãã¯ãšæåçãªç©èªãé
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5. **Subnautica** - ãã®ã²ãŒã ã¯ãçŸããæµ·åºäžçãæ¢çŽ¢ã§ãããµãã€ãã«ã¢ããã³ãã£ãŒã²ãŒã ã§ããã¬ã€ã€ãŒã¯è¬ãããææã®æµ·åºã«äžæçããå®å®è¹ã®ãã€ããããšããŠãçã延ã³ãããã«å¥®éããŸãã
6. **Firewatch** - ãã®ã²ãŒã ã¯ãçŸããèªç¶ã®é¢šæ¯ãèæ¯ã«ã䞻人å
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7. **What remains of Edith Finch** - ãã®ã²ãŒã ã¯ã家æã®ç©èªãéããŠçµéšããã¢ããã³ãã£ãŒã²ãŒã ã§ããã¬ã€ã€ãŒã¯äž»äººå
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8. **Gone Home** - ãã®ã²ãŒã ã¯ã家æã®äžåšãæããã€ã³ã¿ã©ã¯ãã£ããªç©èªäœéšã²ãŒã ã§ããã¬ã€ã€ãŒã¯äž»äººå
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2. ã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ã
3. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®å
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4. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®çžéç¹
5. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹
6. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹ã®èŠçŽ
7. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹ã®èŠçŽ
8. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹ã®èŠçŽ
9. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹ã®èŠçŽ
10. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹ã®èŠçŽ
11. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹ã®èŠçŽ
12. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹ã®èŠçŽ
13. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹ã®èŠçŽ
14. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹ã®èŠçŽ
15. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹ã®èŠçŽ
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17. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹ã®èŠçŽ
18. ãŒã«ãã®äŒèª¬:ãã¬ã¹ãªãã¶ã¯ã€ã«ããšã¢ã ããžã¢:ããŒã¯ãã£ã»ã³ãã®é¡äŒŒç¹ãšçžéç¹ã®èŠçŽ
19. ãŒã«ãã®äŒèª¬:ãã¬ã¹ | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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|
äžããããPythonã®é¢æ°ãã³ã¡ã³ããå«ããŠèª¬æããŠãã ããã | ```python
def calculate_area(radius):
return 3.14 * radius ** 2
``` | ```python
def calculate_area(radius):
"""
ååŸãååŸããŠãåã®é¢ç©ãèšç®ããŸãã
Args:
radius (float): åã®ååŸ
Returns:
float: åã®é¢ç©
"""
return 3.14 * radius ** 2
``` | ```python
def calculate_area(radius):
"""
äžããããååŸã®åã®é¢ç©ãèšç®ããé¢æ°ã§ãã
"""
return 3.14 * radius ** 2
``` | 以äžã¯ãã¿ã¹ã¯ã説æããæ瀺ãšãæèã®ããå
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### å
¥å
```python
def calculate_area(radius):
return 3.14 * radius ** 2
```
### å¿ç
|
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