05: Python Programming : Analyzing SPSS Data with Python
Py-05: Analyzing SPSS Data with Python
#INSTALLING_NECESSARY_LIBRARIES
pip install pandas matplotlib seaborn pyreadstat
#LOAD_NECESSARY_LIBRARIES
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import pyreadstat
#LOAD_YOUR_SPSS_DATA
file_path = "C:/R/LABSTAT/exam_data.sav" #Make sure this path is correct
data_set, meta = pyreadstat.read_sav(file_path)
print("Column names in the dataset:", data_set.columns)
#CREATE_A_FREQUENCY_TABLE
data_set['Charges_group'] = pd.cut(data_set['Charges'], bins=range(0, int(data_set['Charges'].max()) + 5000, 5000))
charges_frequency = data_set['Charges_group'].value_counts().sort_index()
print("Frequency table of Charges:\n", charges_frequency)
#CALCULATE_DESCRIPTIVE_STATISTICS
desc_stats = data_set['Charges'].describe()
print("Descriptive statistics:\n", desc_stats)
#DATA_VISUALIZATION
plt.figure(figsize=(8, 5))
sns.countplot(x='Region', data=data_set)
plt.title("Distribution of Regions")
plt.xlabel("Region")
plt.ylabel("Count")
plt.show()
#BOX_PLOT_FOR_CHARGES
plt.figure(figsize=(8, 5))
sns.boxplot(y=data_set['Charges'])
plt.title("Boxplot of Charges")
plt.ylabel("Charges")
plt.show()
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