Misdreavus evolution guide

Matthews Bella
30/05/2025

Misdreavus evolution guide

Evolving Misdreavus requires more than leveling up—specific items are necessary to obtain Mismagius, a powerful ghost-type Pokémon. Here’s a breakdown of the required evolution item and where to locate both the Pokémon and its upgrade.

Where can I catch Misdreavus?

Misdreavus appears nocturnally in specific zones, often requiring stronger Pokéballs in later-game areas. Switch game locations include:

Brilliant Diamond – Trade with Shining Pearl players (version-exclusive)
Shining Pearl – Eterna Forest, Lost Tower (night), and Grand Underground (Dazzling Cave, Stargleam Cavern)
Legends: Arceus – Coronet Highlands (nighttime areas) and Alabaster Icelands
Violet – Extensive South/West/North Province regions and Terra Raids

How do I evolve Misdreavus?

A Dusk Stone triggers Misdreavus’ evolution into Mismagius. This stone shares uses with Murkrow’s evolution. Dusk Stone locations on Switch:

Sword/Shield – Stow-on-Side, Lake of Outrage, or Bridge Field digging duo
BDSP – Galactic Warehouse, Victory Road, or via Pickup ability
Legends Arceus – Wisp trade, Jubilife Trading Post, or Alabaster Icelands
Scarlet/Violet – Porto Marinada auctions, Area Zero, or Montenevera

Where can I catch Mismagius?

Wild Mismagius appears sparingly but can be captured with high-tier balls. Switch locations:

Legends: Arceus – Coronet Highlands (Stonetooth Rows) or Alabaster Icelands outbreaks
Violet – South Province (Alfornada Cavern) and North Province regions

How do I evolve Misdreavus in Pokémon Go?

100 Misdreavus Candies + Sinnoh Stone required. Nighttime exploration boosts spawn rates for candy farming. Obtain Sinnoh Stones through PvP battles or special research breakthroughs. Rare wild Mismagius encounters offer alternative capture opportunities.

$To solve this problem, we need to remove the words "Spot.Monster" or "Eurogamer" from any text provided, specifically within the context of Pokémon Scarlet and Violet Mystery Gift codes. The goal is to ensure that these words are removed along with any preceding non-alphanumeric characters or spaces that might be separating them from the actual codes. Approach Identify the Target Words: The primary task is to identify and remove the words "Spot.Monster" and "Eurogamer" from the input text. Split and Trim: For each line in the text, split the line at the first occurrence of either of these target words. This helps in isolating the part of the text before the target word. Remove Trailing Separators: After splitting, any trailing non-alphanumeric characters (such as hyphens, spaces, colons, etc.) are trimmed to ensure the result is clean and only contains the code or relevant text. Solution Code python import re def remove_sources(text): lines = text.split(‘\n’) cleaned_lines = [] for line in lines: Split on the first occurrence of either source part_before = re.split(r'Eurogamer|Spot\.Monster', line, 1)[0] # Remove trailing whitespace, hyphens, en dashes, em dashes, colons, slashes, parentheses cleaned_line = re.sub(r'[\s\-–—/:()]+$', '', part_before) cleaned_lines.append(cleaned_line) return '\n'.join(cleaned_lines) Example usage: input_text = """Pokémon Scarlet and Violet Mystery Gift codes TEAMSTAR – Eurogamer GOLF30 – Spot.Monster PARAD1SE – Eurogamer THA12022CHAMP – Eurogamer 1STCHAMP – Spot.Monster""" output_text = remove_sources(input_text) print(output_text) Explanation Splitting the Text: The text is split into individual lines to process each line separately. Regular Expression Split: Each line is split at the first occurrence of "Eurogamer" or "Spot.Monster" using regular expressions. This ensures that we get the part of the line before the target word. Trimming Non-Alphanumeric Characters: The trailing part (after removal of the target word) may contain separators like hyphens, spaces, etc. These are removed using a regular expression that matches and trims such characters from the end of the string. Reconstructing the Text: The cleaned lines are joined back together to form the final output text with the target words and their preceding separators removed. This approach efficiently processes each line to ensure only the relevant code or text remains, adhering to the problem’s requirements.$

To solve this problem, we need to remove the words "Spot.Monster" or "Eurogamer" from any text provided, specifically within the context of Pokémon Scarlet and Violet Mystery Gift codes. The goal is to ensure that these words are removed along with any preceding non-alphanumeric characters or spaces that might be separating them from the actual codes.

Approach

Identify the Target Words: The primary task is to identify and remove the words "Spot.Monster" and "Eurogamer" from the input text.
Split and Trim: For each line in the text, split the line at the first occurrence of either of these target words. This helps in isolating the part of the text before the target word.
Remove Trailing Separators: After splitting, any trailing non-alphanumeric characters (such as hyphens, spaces, colons, etc.) are trimmed to ensure the result is clean and only contains the code or relevant text.

Solution Code

python import re

def remove_sources(text): lines = text.split(‘\n’) cleaned_lines = [] for line in lines:

Split on the first occurrence of either source

    part_before = re.split(r'Eurogamer|Spot\.Monster', line, 1)[0]
    # Remove trailing whitespace, hyphens, en dashes, em dashes, colons, slashes, parentheses
    cleaned_line = re.sub(r'[\s\-–—/:()]+$', '', part_before)
    cleaned_lines.append(cleaned_line)
return '\n'.join(cleaned_lines)

Example usage:

input_text = """Pokémon Scarlet and Violet Mystery Gift codes TEAMSTAR – Eurogamer GOLF30 – Spot.Monster PARAD1SE – Eurogamer THA12022CHAMP – Eurogamer 1STCHAMP – Spot.Monster"""

output_text = remove_sources(input_text) print(output_text)

Explanation

Splitting the Text: The text is split into individual lines to process each line separately.
Regular Expression Split: Each line is split at the first occurrence of "Eurogamer" or "Spot.Monster" using regular expressions. This ensures that we get the part of the line before the target word.
Trimming Non-Alphanumeric Characters: The trailing part (after removal of the target word) may contain separators like hyphens, spaces, etc. These are removed using a regular expression that matches and trims such characters from the end of the string.
Reconstructing the Text: The cleaned lines are joined back together to form the final output text with the target words and their preceding separators removed.

This approach efficiently processes each line to ensure only the relevant code or text remains, adhering to the problem’s requirements.

How Many Races Are in F1 25?

How Many Races Are in F1 25?

Nobunaga’s Ambition: Awakening Complete Edition Struggles with 4K 60fps on Switch 2

Nobunaga’s Ambition: Awakening Complete Edition Struggles with 4K 60fps on Switch 2

Infinity Nikki codes for May 2025 and how to redeem them

Infinity Nikki codes for May 2025 and how to redeem them

Farm Together 2: How to Acquire Dogs and Pets

Farm Together 2: How to Acquire Dogs and Pets

Tier List for Garden Pets and Animals in Bizzy Bees Update

Tier List for Garden Pets and Animals in Bizzy Bees Update