clip Method¶

The clip() method constrains values to a specified range.

Basic Usage¶

Clipping with Lower and Upper Bounds¶

import pandas as pd

s = pd.Series([1, 5, 10, 15, 20, 25])

# Clip values to range [5, 20]
clipped = s.clip(lower=5, upper=20)
print(clipped)

0     5
1     5
2    10
3    15
4    20
5    20
dtype: int64

Only Lower or Upper Bound¶

s.clip(lower=10)  # Values below 10 become 10
s.clip(upper=15)  # Values above 15 become 15

DataFrame Clipping¶

Clip All Columns¶

df = pd.DataFrame({
    'A': [1, 5, 10, 15, 20],
    'B': [2, 8, 14, 22, 30]
})

clipped = df.clip(lower=5, upper=20)
print(clipped)

Per-Column Clipping¶

df = pd.DataFrame({'A': [1, 50, 100], 'B': [10, 500, 1000]})

# Different bounds for each column
clipped = df.clip(lower=[0, 100], upper=[80, 800], axis=1)

Practical Examples¶

1. Outlier Capping¶

def cap_outliers(df, columns):
    """Cap outliers at 1st and 99th percentiles."""
    df_capped = df.copy()
    for col in columns:
        lower = df[col].quantile(0.01)
        upper = df[col].quantile(0.99)
        df_capped[col] = df[col].clip(lower=lower, upper=upper)
    return df_capped

2. Normalizing to Range¶

# Clip values to valid range before processing
scores = pd.Series([95, 105, 88, -5, 72])
valid_scores = scores.clip(lower=0, upper=100)

3. Financial Position Limits¶

positions = pd.DataFrame({
    'ticker': ['AAPL', 'GOOGL', 'MSFT'],
    'weight': [0.45, 0.35, 0.20]
})

# Enforce max 40% position limit
positions['weight_capped'] = positions['weight'].clip(upper=0.40)

4. Signal Processing¶

# Clip noisy sensor readings
readings = pd.Series([98, 102, 150, 95, 99, -10, 101])
clean_readings = readings.clip(lower=90, upper=110)

Key Parameters¶

Parameter	Description	Default
`lower`	Minimum allowed value	None
`upper`	Maximum allowed value	None
`axis`	Align bounds along axis (0 or 1)	None
`inplace`	Modify in place	False

Notes¶

At least one of lower or upper must be specified
NaN values are not clipped (they remain NaN)
Works with both Series and DataFrame
Original data is not modified unless inplace=True