القائمة
SQL queries, spreadsheet analysis, charts, and statistical methods. Use when the user has data to analyze, needs visualizations, or wants insights from CSV/JSON/Excel files.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | data-analyst |
| description | SQL queries, spreadsheet analysis, charts, and statistical methods. Use when the user has data to analyze, needs visualizations, or wants insights from CSV/JSON/Excel files. |
| version | 1.0.0 |
| license | MIT |
| compatibility | Python 3.8+ with pandas, matplotlib, seaborn, scipy |
| metadata | {"author":"hermeshub","hermes":{"tags":["data-analysis","sql","charts","statistics","visualization"],"category":"data","requires_tools":["terminal"]}} |
End-to-end data analysis with visualization and reporting.
import pandas as pd
df = pd.read_csv("data.csv")
print(df.describe())
print(df.info())
print(df.isnull().sum())
import matplotlib.pyplot as plt
import seaborn as sns
# Distribution
sns.histplot(df['column'], kde=True)
# Correlation
sns.heatmap(df.corr(), annot=True)
# Time series
df.plot(x='date', y='value', figsize=(12,6))
plt.savefig('chart.png', dpi=150, bbox_inches='tight')
from scipy import stats
# T-test
t_stat, p_val = stats.ttest_ind(group_a, group_b)
# Correlation
r, p = stats.pearsonr(x, y)
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