51 lines
1.8 KiB
Python
51 lines
1.8 KiB
Python
import pandas as pd
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from typing import List
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def strip_character(column_name, characters: List[str]):
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new_col_name = column_name
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for character in characters:
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new_col_name = new_col_name.replace(character, '')
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new_col_name = new_col_name.strip()
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return new_col_name
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def refine_content(df):
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strip_character_list = [' ', '\n', ':', '：','其他']
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for col in df.columns:
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df[col] = df[col].apply(lambda x: "其他" if strip_character(x, strip_character_list) == "" else strip_character(x, strip_character_list))
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return df
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def get_acv_distribution(df, acv_name, industry_col_name):
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# Define the bins for ACV intervals
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bins = [0, 1e6, 5e6, float('inf')]
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labels = ['<100万', '100万-500万', '>500万']
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# Create a new column 'ACV Interval' based on the bins
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df['ACV Interval'] = pd.cut(df[acv_name], bins=bins, labels=labels, right=False)
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industry_acv_distribution = df.groupby([industry_col_name, 'ACV Interval']).size().unstack(fill_value=0)
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industry_acv_distribution.loc['Total'] = industry_acv_distribution.sum()
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return industry_acv_distribution
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# Define the bins for ACV intervals
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df = pd.read_excel('./data_src/pingcap_won.xlsx')
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print('---------成单:ACV Distribution by industry--------')
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print(get_acv_distribution(df, 'ACV', '客户分类'))
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print('---------成单:ACV Distribution by sub-industry--------')
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print(get_acv_distribution(df, 'ACV', '客户行业'))
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df_pipeline = pd.read_excel('./data_src/pingcap_pipeline.xlsx')
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print('---------Pipeline:ACV Distribution by industry--------')
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print(get_acv_distribution(df_pipeline, '预估 ACV', '负责人所属行业'))
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print('---------Pipeline:ACV Distribution by sub-industry--------')
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print(get_acv_distribution(df_pipeline, '预估 ACV', '客户行业')) |