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Analyze the increase in popularity of a language in the current year … #313

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Jul 3, 2024
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Analyze the increase in popularity of a language in the current year … #313

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60 changes: 48 additions & 12 deletions Stackoverflow_Survey_Analysis.ipynb
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Expand Up @@ -21899,25 +21899,61 @@
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"cell_type": "markdown",
"metadata": {},
"outputs": [],
"source": []
"source": [
"# Analyze the increase in popularity of a language in the current year due to developer’s interest in the previous year. #301"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
"source": [
"import pandas as pd\n",
"\n",
"# Load the CSV files\n",
"file_2022 = pd.read_csv(r\"Data/survey_results_public_2022.csv\")\n",
"file_2023 = pd.read_csv(r\"Data/survey_results_public_2023.csv\")\n",
"\n",
"def preprocess_data(df):\n",
" # Fill missing values in relevant columns\n",
" df['LanguageWorkedWith'] = df['LanguageWorkedWith'].fillna('')\n",
" df['LanguageDesireNextYear'] = df['LanguageDesireNextYear'].fillna('')\n",
" return df\n",
"\n",
"# Preprocess the data\n",
"data_2022 = preprocess_data(file_2022)\n",
"data_2023 = preprocess_data(file_2023)\n",
"\n",
"# Function to count the occurrences of each language\n",
"def count_languages(df, column):\n",
" languages = df[column].str.split(';').explode().str.strip()\n",
" return languages.value_counts()\n",
"\n",
"# Count languages for both years\n",
"lang_count_2022 = count_languages(data_2022, 'LanguageWorkedWith')\n",
"lang_desire_2022 = count_languages(data_2022, 'LanguageDesireNextYear')\n",
"lang_count_2023 = count_languages(data_2023, 'LanguageWorkedWith')\n",
"\n",
"# Convert to DataFrame for easier comparison\n",
"lang_count_2022_df = lang_count_2022.reset_index().rename(columns={'index': 'Language', 'LanguageWorkedWith': 'Count_2022'})\n",
"lang_desire_2022_df = lang_desire_2022.reset_index().rename(columns={'index': 'Language', 'LanguageDesireNextYear': 'Desire_2022'})\n",
"lang_count_2023_df = lang_count_2023.reset_index().rename(columns={'index': 'Language', 'LanguageWorkedWith': 'Count_2023'})\n",
"\n",
"# Merge the dataframes\n",
"merged_df = lang_count_2022_df.merge(lang_desire_2022_df, on='Language', how='outer').merge(lang_count_2023_df, on='Language', how='outer').fillna(0)\n",
"\n",
"# Calculate the increase in popularity\n",
"merged_df['Increase'] = merged_df['Count_2023'] - merged_df['Count_2022']\n",
"merged_df['Interest_to_Popularity'] = (merged_df['Count_2023'] - merged_df['Count_2022']) / merged_df['Desire_2022']\n",
"\n",
"# Sort by the increase in popularity\n",
"merged_df = merged_df.sort_values(by='Increase', ascending=False)\n",
"\n",
"print(merged_df[['Language', 'Count_2022', 'Desire_2022', 'Count_2023', 'Increase', 'Interest_to_Popularity']])\n"
]
},
{
"cell_type": "markdown",
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