diff --git a/1.py b/1.py
new file mode 100644
index 0000000000000000000000000000000000000000..162291542ae31e1330bce3e2efc574f47dbcb5f6
--- /dev/null
+++ b/1.py
@@ -0,0 +1,106 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+
+# 加载数据集
+file_path = 'C:\Users\A\Desktop\分行业机器人数据.dta'
+data = pd.read_stata(file_path)
+
+# 设置绘图的美观风格
+sns.set_style("whitegrid")
+
+# 整体趋势
+# 按年汇总安装量和运营库存
+overall_trend = data.groupby('year').agg({'installations': 'sum', 'operationalstock': 'sum'}).reset_index()
+
+# Plotting the overall trends
+plt.figure(figsize=(12, 6))
+plt.plot(overall_trend['year'], overall_trend['installations'], label='Installations', marker='o')
+plt.plot(overall_trend['year'], overall_trend['operationalstock'], label='Operational Stock', marker='x')
+plt.title('Global Industrial Robots: Overall Trends')
+plt.xlabel('Year')
+plt.ylabel('Count')
+plt.legend()
+plt.show()
+
+overall_trend.tail() # 显示最近几年的趋势以便快速查看
+
+# 按国家分布
+country_distribution = data.groupby('Country').agg({'installations': 'sum', 'operationalstock': 'sum'}).reset_index()
+country_distribution.sort_values(by='installations', ascending=False, inplace=True)
+
+# 绘制按国家分布的图
+plt.figure(figsize=(15, 8))
+sns.barplot(x='installations', y='Country', data=country_distribution.head(10))
+plt.title('Top 10 Countries by Industrial Robot Installations')
+plt.xlabel('Total Installations')
+plt.ylabel('Country')
+plt.show()
+
+# 按行业分布
+industry_distribution = data.groupby('Industry').agg({'installations': 'sum', 'operationalstock': 'sum'}).reset_index()
+industry_distribution.sort_values(by='installations', ascending=False, inplace=True)
+
+# 绘制按行业分布的图
+plt.figure(figsize=(15, 8))
+sns.barplot(x='installations', y='Industry', data=industry_distribution.head(10))
+plt.title('Top 10 Industries by Industrial Robot Installations')
+plt.xlabel('Total Installations')
+plt.ylabel('Industry')
+plt.show()
+
+(country_distribution.head(10), industry_distribution.head(10)) # 显示安装量前10的国家和行业以便快速查看
+
+
+# 重点国家：中国、日本、美国
+key_countries = ['China', 'Japan', 'United States']
+key_countries_data = data[data['Country'].isin(key_countries)]
+
+# 重点国家的趋势分析
+key_countries_trend = key_countries_data.groupby(['year', 'Country']).agg({'installations': 'sum', 'operationalstock': 'sum'}).reset_index()
+
+# 绘制重点国家趋势图
+plt.figure(figsize=(15, 8))
+sns.lineplot(x='year', y='installations', hue='Country', data=key_countries_trend, marker='o')
+plt.title('Trend of Industrial Robot Installations in Key Countries')
+plt.xlabel('Year')
+plt.ylabel('Installations')
+plt.legend(title='Country')
+plt.show()
+
+# 重点行业：汽车和电子/电气
+key_industries = ['Automotive', 'Electrical/electronics']
+key_industries_data = data[data['Industry'].isin(key_industries)]
+
+# 重点行业的趋势分析
+key_industries_trend = key_industries_data.groupby(['year', 'Industry']).agg({'installations': 'sum', 'operationalstock': 'sum'}).reset_index()
+
+# 绘制重点行业趋势图
+plt.figure(figsize=(15, 8))
+sns.lineplot(x='year', y='installations', hue='Industry', data=key_industries_trend, marker='o')
+plt.title('Trend of Industrial Robot Installations in Key Industries')
+plt.xlabel('Year')
+plt.ylabel('Installations')
+plt.legend(title='Industry')
+plt.show()
+
+(key_countries_trend.head(), key_industries_trend.head()) # 显示每个重点分析的前几行以便快速查看
+
+# 从原始数据集重新加载全球安装量数据
+global_data = data.groupby('year')['installations'].sum()
+
+# 重新计算全球安装量的年增长率
+global_data_growth = global_data.pct_change().dropna() * 100  # 转换为百分比
+
+# 重新绘制年增长率图
+plt.figure(figsize=(14, 7))
+plt.plot(global_data_growth.index, global_data_growth, label='Year-Over-Year Growth Rate', marker='o', linestyle='-')
+plt.title('Year-Over-Year Growth Rate of Global Industrial Robot Installations')
+plt.xlabel('Year')
+plt.ylabel('Growth Rate (%)')
+plt.legend()
+plt.grid(True)
+plt.show()
+
+global_data_growth.describe()  # 提供增长率的统计摘要