diff --git a/scipy.signal_butterworth/README.md b/scipy.signal_butterworth/README.md
index 90a7c87..6d2c1cc 100644
--- a/scipy.signal_butterworth/README.md
+++ b/scipy.signal_butterworth/README.md
@@ -39,3 +39,90 @@ plt.ylabel("Waveform shifted")
 plt.title("unfiltered data")
 plt.show()
 ```
+![figure 1](figure_1.png)
+
+## Low pass
+
+```python
+from scipy import signal
+
+lowpass_frequency = 2.0  # Hz
+
+# Nint : The order of the filter.
+# Wn : The critical frequency or frequencies. For lowpass and highpass filters, Wn is a scalar; for bandpass and bandstop filters, Wn is a length-2 sequence.
+# For a Butterworth filter, this is the point at which the gain drops to 1/sqrt(2) that of the passband (the “-3 dB point”).
+# For digital filters, if fs is not specified, Wn units are normalized from 0 to 1, where 1 is the Nyquist frequency (Wn is thus in half cycles / sample and defined as 2*critical frequencies / fs). If fs is specified, Wn is in the same units as fs.
+# For analog filters, Wn is an angular frequency (e.g. rad/s).
+# btype{‘lowpass’, ‘highpass’, ‘bandpass’, ‘bandstop’}, optional
+# fs float, optional : The sampling frequency of the digital system.
+b_low, a_low = signal.butter(
+    N=4, Wn=lowpass_frequency, btype="lowpass", fs=samples_per_second
+)
+sin_low_lp = signal.filtfilt(b_low, a_low, sin_low)
+sin_mid_lp = signal.filtfilt(b_low, a_low, sin_mid)
+sin_high_lp = signal.filtfilt(b_low, a_low, sin_high)
+
+plt.figure(2)
+plt.plot(t, sin_low_lp)
+plt.plot(t, sin_mid_lp + 3)
+plt.plot(t, sin_high_lp + 6)
+plt.xlabel("Time [s]")
+plt.ylabel("Waveform shifted")
+plt.title(f"{lowpass_frequency} Hz low-pass filtered data")
+plt.show()
+```
+![figure 2](figure_2.png)
+
+## High pass
+
+```python
+from scipy import signal
+
+highpass_frequency = 20.0  # Hz
+
+b_high, a_high = signal.butter(
+    N=4, Wn=highpass_frequency, btype="highpass", fs=samples_per_second
+)
+sin_low_hp = signal.filtfilt(b_high, a_high, sin_low)
+sin_mid_hp = signal.filtfilt(b_high, a_high, sin_mid)
+sin_high_hp = signal.filtfilt(b_high, a_high, sin_high)
+
+plt.figure(3)
+plt.plot(t, sin_low_hp)
+plt.plot(t, sin_mid_hp + 3)
+plt.plot(t, sin_high_hp + 6)
+plt.xlabel("Time [s]")
+plt.ylabel("Waveform shifted")
+plt.title(f"{highpass_frequency} Hz high-pass filtered data")
+plt.show()
+```
+![figure 3](figure_3.png)
+
+## Band pass
+
+```python
+from scipy import signal
+
+lowpass_frequency = 2.0  # Hz
+highpass_frequency = 20.0  # Hz
+
+b_band, a_band = signal.butter(
+    N=4,
+    Wn=(lowpass_frequency, highpass_frequency),
+    btype="bandpass",
+    fs=samples_per_second,
+)
+sin_low_bp = signal.filtfilt(b_band, a_band, sin_low)
+sin_mid_bp = signal.filtfilt(b_band, a_band, sin_mid)
+sin_high_bp = signal.filtfilt(b_band, a_band, sin_high)
+
+plt.figure(4)
+plt.plot(t, sin_low_bp)
+plt.plot(t, sin_mid_bp + 3)
+plt.plot(t, sin_high_bp + 6)
+plt.xlabel("Time [s]")
+plt.ylabel("Waveform shifted")
+plt.title(f"({lowpass_frequency} Hz, {highpass_frequency} Hz) band-pass filtered data")
+plt.show()
+```
+![figure 4](figure_4.png)