To analyze the trends in the volume of negotiation and the feeling of the market for Litecoin (LTC), we will use the data from Kraken, a renowned cryptocurrency exchange. We will focus on the last 30 days to seize the current market conditions.

Trading volume analysis

Trading volume is a crucial indicator of market demand and potential purchase or sale pressure. Here is how we can analyze trends in the trading volume for Litecoin:

`Python

Import pandas as a PD

Import yfinance as yf

Download historical data

Litecoin = yf.ticher ('ltc')

Data = Litecoin.History (period = '30d')

Group per day to calculate the daily sum of the volume (volume exchanged)

Volume_data = data.groupby (pd.group (key = data.index, freq = "d") ['close']. Sum (). Reset_index ()

Calculate trading volume trends

Volume_trend = volume_data ['volume'].

Print (volume_trend)

'

This code calculates the daily sum of the volume of trading for Litecoin, then a rolling window to calculate the volume of trading of the ad for periods of 20 days. This can help identify potential trends in buying or selling pressure.

Analysis of the market feeling

The feeling of the market is also an important factor when analyzing the price and volumes of cryptocurrencies. Here's how we can analyze the feeling of the market for Litecoin:

Python

Import pandas as a PD

from the Yfinance import download

from textblob import textblob

Download historical data

Litecoin = yf.ticher ('ltc')

Data = Litecoin.History (period = '30d')

Calculate the feeling of the market using the TextBlob library

df = data ["close"].

Feeling_Scores = df.apply (lambda x: textblob (x) .polarity)

Print scores for each day

For I in the range (len (feeling_scores)):

Print (f "day {i + 1}: {feeling_scores.iloc [i] .polarity: .2f}"))

` ‘

This code calculates the average closing price over 30 -day periods, then using textblob to analyze the marketing market. The polarity score varies from -1 (very negative) to 1 (very positive). A high polarity score may indicate high purchase or sale pressure.

Example of use cases

– Analysis of trends in the volume of negotiation can help traders identify the potential areas of support or resistance in the action of Litecoin prices.

– Analysis of the feeling of the market can give an overview of market psychology and potential catalysts at Litecoin prices.

These are basic examples to start analyzing trends in the commercial volume and the feeling of the market. While you continue to find out more about the cryptocurrency markets, you can meet various tools and techniques that can help refine your analytical skills.

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