everfern-ai/everfern/csv

import pandas as pd
# Read CSV
df = pd.read_csv(r'C:\path\to\file.csv')
# Preview data
print(df.head())           # First 5 rows
print(df.info())           # Column info and types
print(df.describe())       # Statistical summary
print(df.shape)            # Rows and columns count
print(df.columns.tolist()) # Column names
# Analyze data
print(df['ColumnName'].value_counts())  # Count unique values
print(df.isnull().sum())                # Missing values

df_clean = df.drop_duplicates()
df_clean.to_csv(r'C:\path\to\output.csv', index=False)

filtered = df[df['ColumnName'] > 100]
filtered.to_csv(r'C:\path\to\filtered.csv', index=False)

selected = df[['Column1', 'Column2', 'Column3']]
selected.to_csv(r'C:\path\to\selected.csv', index=False)

# Remove rows with missing values
df_clean = df.dropna()
# Fill missing values
df_filled = df.fillna(0)  # Fill with 0
df_filled = df.fillna(df.mean())  # Fill with column mean
df_filled.to_csv(r'C:\path\to\output.csv', index=False)

import pandas as pd
data = {
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [25, 30, 35],
    'City': ['NYC', 'LA', 'Chicago']
}
df = pd.DataFrame(data)
df.to_csv(r'C:\path\to\new_file.csv', index=False)

import csv
data = [
    ['Name', 'Email', 'Phone'],
    ['John', 'john@example.com', '123-456-7890'],
    ['Jane', 'jane@example.com', '098-765-4321']
]
with open(r'C:\path\to\file.csv', 'w', newline='') as f:
    writer = csv.writer(f)
    writer.writerows(data)

# Group by a column and calculate statistics
summary = df.groupby('Category')['Amount'].sum()
summary.to_csv(r'C:\path\to\summary.csv')
# Multiple aggregations
summary = df.groupby('Category').agg({
    'Amount': 'sum',
    'Count': 'count',
    'Average': 'mean'
})
summary.to_csv(r'C:\path\to\summary.csv')

df1 = pd.read_csv(r'C:\path\to\file1.csv')
df2 = pd.read_csv(r'C:\path\to\file2.csv')
# Concatenate rows
merged = pd.concat([df1, df2], ignore_index=True)
# Merge by common column
merged = pd.merge(df1, df2, on='CommonColumn')
merged.to_csv(r'C:\path\to\merged.csv', index=False)

# Tab-separated
df.to_csv(r'C:\path\to\file.tsv', sep='\t', index=False)
# With encoding
df.to_csv(r'C:\path\to\file.csv', index=False, encoding='utf-8')
# Custom delimiter
df.to_csv(r'C:\path\to\file.csv', sep=';', index=False)