def get_top_volume_coins() -> pd.DataFrame:
"""Scrapes top coins by trading volume "https://www.coingecko.com/en/coins/high_volume"
Returns
-------
pandas.DataFrame
Rank, Name, Symbol, Price, Change_1h, Change_24h, Change_7d, Volume_24h, Market_Cap
"""
columns = [
"Rank",
"Name",
"Symbol",
"Price",
"Change_1h",
"Change_24h",
"Change_7d",
"Volume_24h",
"Market_Cap",
]
url = "https://www.coingecko.com/en/coins/high_volume"
rows = scrape_gecko_data(url).find("tbody").find_all("tr")
results = []
for row in rows:
row_cleaned = clean_row(row)
if len(row_cleaned) == 9:
row_cleaned.insert(0, "?")
row_cleaned.pop(3)
results.append(row_cleaned)
df = replace_qm(pd.DataFrame(results, columns=columns))
df.drop("Rank", axis=1, inplace=True)
create_df_index(df, "Rank")
df["Price"] = df["Price"].apply(lambda x: float(x.strip("$").replace(",", "")))
return df
def get_stable_coins() -> pd.DataFrame:
"""Scrapes stable coins data from "https://www.coingecko.com/en/stablecoins" [Source: CoinGecko]
Returns
-------
pandas.DataFrame
Rank, Name, Symbol, Price, Change_24h, Exchanges, Market_Cap, Change_30d, Url
"""
columns = [
"Rank",
"Name",
"Symbol",
"Price",
"Change_24h",
"Exchanges",
"Market_Cap",
"Change_30d",
"Url",
]
url = "https://www.coingecko.com/en/stablecoins"
rows = scrape_gecko_data(url).find("tbody").find_all("tr")
results = []
for row in rows:
link = GECKO_BASE_URL + row.find("a")["href"]
row_cleaned = clean_row(row)
if len(row_cleaned) == 8:
row_cleaned.append(None)
(
rank,
name,
*symbols,
price,
volume_24h,
exchanges,
market_cap,
change_30d,
) = row_cleaned
symbol = symbols[0] if symbols else symbols
results.append([
rank,
name,
symbol,
price,
volume_24h,
exchanges,
market_cap,
change_30d,
link,
])
df = replace_qm(pd.DataFrame(results, columns=columns))
df.drop("Rank", axis=1, inplace=True)
create_df_index(df, "Rank")
df["Price"] = df["Price"].apply(
lambda x: float(x.strip("$").replace(",", "")))
return df
def get_recently_added_coins() -> pd.DataFrame:
"""Scrape recently added coins on CoinGecko from "https://www.coingecko.com/en/coins/recently_added"
[Source: CoinGecko]
Returns
-------
pandas.DataFrame
Recently Added Coins on CoinGecko
Columns: Name, Symbol, Price, Change_1h, Change_24h, Added
"""
columns = [
"Name",
"Symbol",
"Price",
"Change_1h",
"Change_24h",
"Added",
"Url",
]
url = "https://www.coingecko.com/en/coins/recently_added"
try:
scraped_data = scrape_gecko_data(url)
except RetryError as e:
print(e)
return pd.DataFrame()
rows = scraped_data.find("tbody").find_all("tr")
results = []
for row in rows:
url = GECKO_BASE_URL + row.find("a")["href"]
row_cleaned = clean_row(row)
(
name,
symbol,
_,
price,
*changes,
_,
_volume,
last_added,
) = row_cleaned
change_1h, change_24h, _ = changes_parser(changes)
results.append(
[name, symbol, price, change_1h, change_24h, last_added, url])
df = replace_qm(pd.DataFrame(results, columns=columns))
df.index = df.index + 1
df.reset_index(inplace=True)
df.rename(columns={"index": "Rank"}, inplace=True)
df["Price"] = df["Price"].apply(
lambda x: float(x.strip("$").replace(",", "")))
return df