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ivirshup/anndata-pypi-downloads.svg

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pypi-downloads-historical.ipynb
{
"cells": [
{
"cell_type": "markdown",
"id": "81396303-8753-4cb2-80d9-af786413be3c",
"metadata": {},
"source": [
"# PYPI downloads historical"
]
},
{
"cell_type": "markdown",
"id": "65d7ef54-f110-4f36-b31e-99b017e09c77",
"metadata": {},
"source": [
"Using the query:\n",
"\n",
"\n",
"```sql\n",
"#standardSQL\n",
"SELECT\n",
" COUNT(*) AS num_downloads,\n",
" DATE_TRUNC(DATE(timestamp), DAY) AS `day`,\n",
" -- DATE_TRUNC(DATE(timestamp), MONTH) AS `month`,\n",
" file.project\n",
"FROM `bigquery-public-data.pypi.file_downloads`\n",
"WHERE\n",
" file.project IN ('anndata', 'scanpy', 'scvi-tools', 'squidpy', 'scirpy', 'mudata', 'muon')\n",
" AND DATE(timestamp)\n",
" -- BETWEEN DATE_TRUNC(DATE_SUB(CURRENT_DATE(), INTERVAL 1 WEEK), DAY)\n",
" BETWEEN DATE_TRUNC(DATE_SUB(CURRENT_DATE(), INTERVAL 8 YEAR), DAY)\n",
" AND CURRENT_DATE()\n",
"GROUP BY `day`, file.project\n",
"ORDER BY `day` DESC\n",
"-- GROUP BY `month`, file.project\n",
"-- ORDER BY `month` DESC\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "7d9be52d-1ebb-436a-a236-4fdb5fea35c6",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "e0a696cc-9441-4d43-b79e-76d327ce07ee",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>num_downloads</th>\n",
" <th>day</th>\n",
" <th>project</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>3920</td>\n",
" <td>2023-09-21</td>\n",
" <td>anndata</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2510</td>\n",
" <td>2023-09-21</td>\n",
" <td>scanpy</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>94</td>\n",
" <td>2023-09-21</td>\n",
" <td>squidpy</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>928</td>\n",
" <td>2023-09-21</td>\n",
" <td>mudata</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>51</td>\n",
" <td>2023-09-21</td>\n",
" <td>scirpy</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10188</th>\n",
" <td>543</td>\n",
" <td>2016-05-27</td>\n",
" <td>muon</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10189</th>\n",
" <td>275</td>\n",
" <td>2016-05-26</td>\n",
" <td>muon</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10190</th>\n",
" <td>416</td>\n",
" <td>2016-05-25</td>\n",
" <td>muon</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10191</th>\n",
" <td>20</td>\n",
" <td>2016-05-24</td>\n",
" <td>muon</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10192</th>\n",
" <td>227</td>\n",
" <td>2016-05-23</td>\n",
" <td>muon</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>10193 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" num_downloads day project\n",
"0 3920 2023-09-21 anndata\n",
"1 2510 2023-09-21 scanpy\n",
"2 94 2023-09-21 squidpy\n",
"3 928 2023-09-21 mudata\n",
"4 51 2023-09-21 scirpy\n",
"... ... ... ...\n",
"10188 543 2016-05-27 muon\n",
"10189 275 2016-05-26 muon\n",
"10190 416 2016-05-25 muon\n",
"10191 20 2016-05-24 muon\n",
"10192 227 2016-05-23 muon\n",
"\n",
"[10193 rows x 3 columns]"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.read_csv(\"2023-09-21-pypi-downloads.csv\", dtype={\"project\": pd.CategoricalDtype()}, parse_dates=[\"day\"])\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "43be8da3-92e8-4942-abd6-b0b26aeef43f",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>num_downloads</th>\n",
" <th>day</th>\n",
" <th>project</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>3920</td>\n",
" <td>2023-09-21</td>\n",
" <td>anndata</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7764</th>\n",
" <td>578</td>\n",
" <td>2020-03-23</td>\n",
" <td>anndata</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7762</th>\n",
" <td>549</td>\n",
" <td>2020-03-24</td>\n",
" <td>anndata</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7760</th>\n",
" <td>659</td>\n",
" <td>2020-03-25</td>\n",
" <td>anndata</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7756</th>\n",
" <td>847</td>\n",
" <td>2020-03-26</td>\n",
" <td>anndata</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2270</th>\n",
" <td>86</td>\n",
" <td>2022-11-01</td>\n",
" <td>squidpy</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5445</th>\n",
" <td>25</td>\n",
" <td>2021-08-02</td>\n",
" <td>squidpy</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3225</th>\n",
" <td>17</td>\n",
" <td>2022-06-18</td>\n",
" <td>squidpy</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5433</th>\n",
" <td>34</td>\n",
" <td>2021-08-04</td>\n",
" <td>squidpy</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2767</th>\n",
" <td>61</td>\n",
" <td>2022-08-22</td>\n",
" <td>squidpy</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>10193 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" num_downloads day project\n",
"0 3920 2023-09-21 anndata\n",
"7764 578 2020-03-23 anndata\n",
"7762 549 2020-03-24 anndata\n",
"7760 659 2020-03-25 anndata\n",
"7756 847 2020-03-26 anndata\n",
"... ... ... ...\n",
"2270 86 2022-11-01 squidpy\n",
"5445 25 2021-08-02 squidpy\n",
"3225 17 2022-06-18 squidpy\n",
"5433 34 2021-08-04 squidpy\n",
"2767 61 2022-08-22 squidpy\n",
"\n",
"[10193 rows x 3 columns]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.sort_values(\"project\")"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "f9739d55-f5fc-4f16-a52e-1a4526f35c67",
"metadata": {},
"outputs": [],
"source": [
"anndata_df = df[df[\"project\"] == \"anndata\"]"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "47261031-8279-444b-a58e-3b71910bc0c5",
"metadata": {},
"outputs": [],
"source": [
"anndata_df = anndata_df.sort_values(\"day\")\n",
"anndata_df[\"total_downloads\"] = anndata_df[\"num_downloads\"].cumsum()"
]
},
{
"cell_type": "markdown",
"id": "a3f705dc-8957-4803-a19d-743e81423c81",
"metadata": {},
"source": [
"Plot after removing outlier"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "9c858876-f4f4-4268-b86a-30ef9df82825",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3187"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"anndata_df[\"num_downloads\"].idxmax()"
]
},
{
"cell_type": "code",
"execution_count": 56,
"id": "c1a6cff8-9d30-4fe4-8855-df99a5960b81",
"metadata": {},
"outputs": [],
"source": [
"anndata_df_filtered = anndata_df[anndata_df[\"num_downloads\"] < 100_000]"
]
},
{
"cell_type": "code",
"execution_count": 57,
"id": "eefc2d9a-4482-48f0-9e40-f5e00fe9fb70",
"metadata": {},
"outputs": [],
"source": [
"anndata_df_filtered = anndata_df_filtered.set_index(\"day\")\n",
"anndata_df_filtered[\"total_downloads\"] = anndata_df_filtered[\"num_downloads\"].cumsum()"
]
},
{
"cell_type": "code",
"execution_count": 60,
"id": "95b5792a-0e63-418a-b56f-e8c244a21704",
"metadata": {},
"outputs": [],
"source": [
"import altair as alt"
]
},
{
"cell_type": "code",
"execution_count": 75,
"id": "1d34b4d7-59e6-4131-be9d-7ecb23256366",
"metadata": {},
"outputs": [
{
"data": {
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" const paths = {\n",
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{\"Time\": \"2018-01-07T00:00:00\", \"Weekly Downloads\": 1080}, {\"Time\": \"2018-01-14T00:00:00\", \"Weekly Downloads\": 384}, {\"Time\": \"2018-01-21T00:00:00\", \"Weekly Downloads\": 400}, {\"Time\": \"2018-01-28T00:00:00\", \"Weekly Downloads\": 463}, {\"Time\": \"2018-02-04T00:00:00\", \"Weekly Downloads\": 270}, {\"Time\": \"2018-02-11T00:00:00\", \"Weekly Downloads\": 981}, {\"Time\": \"2018-02-18T00:00:00\", \"Weekly Downloads\": 741}, {\"Time\": \"2018-02-25T00:00:00\", \"Weekly Downloads\": 422}, {\"Time\": \"2018-03-04T00:00:00\", \"Weekly Downloads\": 610}, {\"Time\": \"2018-03-11T00:00:00\", \"Weekly Downloads\": 381}, {\"Time\": \"2018-03-18T00:00:00\", \"Weekly Downloads\": 245}, {\"Time\": \"2018-03-25T00:00:00\", \"Weekly Downloads\": 586}, {\"Time\": \"2018-04-01T00:00:00\", \"Weekly Downloads\": 559}, {\"Time\": \"2018-04-08T00:00:00\", \"Weekly Downloads\": 591}, {\"Time\": \"2018-04-15T00:00:00\", \"Weekly Downloads\": 427}, {\"Time\": \"2018-04-22T00:00:00\", \"Weekly Downloads\": 370}, {\"Time\": \"2018-04-29T00:00:00\", \"Weekly Downloads\": 637}, {\"Time\": \"2018-05-06T00:00:00\", \"Weekly Downloads\": 377}, {\"Time\": \"2018-05-13T00:00:00\", \"Weekly Downloads\": 348}, {\"Time\": \"2018-05-20T00:00:00\", \"Weekly Downloads\": 450}, {\"Time\": \"2018-05-27T00:00:00\", \"Weekly Downloads\": 775}, {\"Time\": \"2018-06-03T00:00:00\", \"Weekly Downloads\": 652}, {\"Time\": \"2018-06-10T00:00:00\", \"Weekly Downloads\": 485}, {\"Time\": \"2018-06-17T00:00:00\", \"Weekly Downloads\": 623}, {\"Time\": \"2018-06-24T00:00:00\", \"Weekly Downloads\": 270}, {\"Time\": \"2018-07-01T00:00:00\", \"Weekly Downloads\": 465}, {\"Time\": \"2018-07-08T00:00:00\", \"Weekly Downloads\": 388}, {\"Time\": \"2018-07-15T00:00:00\", \"Weekly Downloads\": 351}, {\"Time\": \"2018-07-22T00:00:00\", \"Weekly Downloads\": 93}, {\"Time\": \"2018-07-29T00:00:00\", \"Weekly Downloads\": 458}, {\"Time\": \"2018-08-05T00:00:00\", \"Weekly Downloads\": 1840}, {\"Time\": \"2018-08-12T00:00:00\", \"Weekly Downloads\": 1668}, {\"Time\": \"2018-08-19T00:00:00\", \"Weekly Downloads\": 1630}, {\"Time\": \"2018-08-26T00:00:00\", \"Weekly Downloads\": 1327}, {\"Time\": \"2018-09-02T00:00:00\", \"Weekly Downloads\": 1266}, {\"Time\": \"2018-09-09T00:00:00\", \"Weekly Downloads\": 1730}, {\"Time\": \"2018-09-16T00:00:00\", \"Weekly Downloads\": 1549}, {\"Time\": \"2018-09-23T00:00:00\", \"Weekly Downloads\": 2040}, {\"Time\": \"2018-09-30T00:00:00\", \"Weekly Downloads\": 1547}, {\"Time\": \"2018-10-07T00:00:00\", \"Weekly Downloads\": 2042}, {\"Time\": \"2018-10-14T00:00:00\", \"Weekly Downloads\": 5593}, {\"Time\": \"2018-10-21T00:00:00\", \"Weekly Downloads\": 1473}, {\"Time\": \"2018-10-28T00:00:00\", \"Weekly Downloads\": 1667}, {\"Time\": \"2018-11-04T00:00:00\", \"Weekly Downloads\": 2066}, {\"Time\": \"2018-11-11T00:00:00\", \"Weekly Downloads\": 1522}, {\"Time\": \"2018-11-18T00:00:00\", \"Weekly Downloads\": 1754}, {\"Time\": \"2018-11-25T00:00:00\", \"Weekly Downloads\": 1233}, {\"Time\": \"2018-12-02T00:00:00\", \"Weekly Downloads\": 1742}, {\"Time\": \"2018-12-09T00:00:00\", \"Weekly Downloads\": 1694}, {\"Time\": \"2018-12-16T00:00:00\", \"Weekly Downloads\": 2991}, {\"Time\": \"2018-12-23T00:00:00\", \"Weekly Downloads\": 1620}, {\"Time\": \"2018-12-30T00:00:00\", \"Weekly Downloads\": 584}, {\"Time\": \"2019-01-06T00:00:00\", \"Weekly Downloads\": 1473}, {\"Time\": \"2019-01-13T00:00:00\", \"Weekly Downloads\": 1647}, {\"Time\": \"2019-01-20T00:00:00\", \"Weekly Downloads\": 1310}, {\"Time\": \"2019-01-27T00:00:00\", \"Weekly Downloads\": 2251}, {\"Time\": \"2019-02-03T00:00:00\", \"Weekly Downloads\": 3149}, {\"Time\": \"2019-02-10T00:00:00\", \"Weekly Downloads\": 1954}, {\"Time\": \"2019-02-17T00:00:00\", \"Weekly Downloads\": 1750}, {\"Time\": \"2019-02-24T00:00:00\", \"Weekly Downloads\": 1372}, {\"Time\": \"2019-03-03T00:00:00\", \"Weekly Downloads\": 2327}, {\"Time\": \"2019-03-10T00:00:00\", \"Weekly Downloads\": 2219}, {\"Time\": \"2019-03-17T00:00:00\", \"Weekly Downloads\": 2314}, {\"Time\": \"2019-03-24T00:00:00\", \"Weekly Downloads\": 1944}, {\"Time\": \"2019-03-31T00:00:00\", \"Weekly Downloads\": 2369}, {\"Time\": \"2019-04-07T00:00:00\", \"Weekly Downloads\": 2154}, {\"Time\": \"2019-04-14T00:00:00\", \"Weekly Downloads\": 2194}, {\"Time\": \"2019-04-21T00:00:00\", \"Weekly Downloads\": 1505}, {\"Time\": \"2019-04-28T00:00:00\", \"Weekly Downloads\": 1283}, {\"Time\": \"2019-05-05T00:00:00\", \"Weekly Downloads\": 2064}, {\"Time\": \"2019-05-12T00:00:00\", \"Weekly Downloads\": 2719}, {\"Time\": \"2019-05-19T00:00:00\", \"Weekly Downloads\": 2683}, {\"Time\": \"2019-05-26T00:00:00\", \"Weekly Downloads\": 2060}, {\"Time\": \"2019-06-02T00:00:00\", \"Weekly Downloads\": 2949}, {\"Time\": \"2019-06-09T00:00:00\", \"Weekly Downloads\": 2548}, {\"Time\": \"2019-06-16T00:00:00\", \"Weekly Downloads\": 3232}, {\"Time\": \"2019-06-23T00:00:00\", \"Weekly Downloads\": 2859}, {\"Time\": \"2019-06-30T00:00:00\", \"Weekly Downloads\": 1907}, {\"Time\": \"2019-07-07T00:00:00\", \"Weekly Downloads\": 2569}, {\"Time\": \"2019-07-14T00:00:00\", \"Weekly Downloads\": 3275}, {\"Time\": \"2019-07-21T00:00:00\", \"Weekly Downloads\": 2342}, {\"Time\": \"2019-07-28T00:00:00\", \"Weekly Downloads\": 2443}, {\"Time\": \"2019-08-04T00:00:00\", \"Weekly Downloads\": 2977}, {\"Time\": \"2019-08-11T00:00:00\", \"Weekly Downloads\": 2479}, {\"Time\": \"2019-08-18T00:00:00\", \"Weekly Downloads\": 1914}, {\"Time\": \"2019-08-25T00:00:00\", \"Weekly Downloads\": 2048}, {\"Time\": \"2019-09-01T00:00:00\", \"Weekly Downloads\": 1842}, {\"Time\": \"2019-09-08T00:00:00\", \"Weekly Downloads\": 2529}, {\"Time\": \"2019-09-15T00:00:00\", \"Weekly Downloads\": 2649}, {\"Time\": \"2019-09-22T00:00:00\", \"Weekly Downloads\": 2297}, {\"Time\": \"2019-09-29T00:00:00\", \"Weekly Downloads\": 1782}, {\"Time\": \"2019-10-06T00:00:00\", \"Weekly Downloads\": 2783}, {\"Time\": \"2019-10-13T00:00:00\", \"Weekly Downloads\": 1754}, {\"Time\": \"2019-10-20T00:00:00\", \"Weekly Downloads\": 2371}, {\"Time\": \"2019-10-27T00:00:00\", \"Weekly Downloads\": 2519}, {\"Time\": \"2019-11-03T00:00:00\", \"Weekly Downloads\": 2439}, {\"Time\": \"2019-11-10T00:00:00\", \"Weekly Downloads\": 2577}, {\"Time\": \"2019-11-17T00:00:00\", \"Weekly Downloads\": 2118}, {\"Time\": \"2019-11-24T00:00:00\", \"Weekly Downloads\": 2551}, {\"Time\": \"2019-12-01T00:00:00\", \"Weekly Downloads\": 1951}, {\"Time\": \"2019-12-08T00:00:00\", \"Weekly Downloads\": 1971}, {\"Time\": \"2019-12-15T00:00:00\", \"Weekly Downloads\": 2456}, {\"Time\": \"2019-12-22T00:00:00\", \"Weekly Downloads\": 2345}, {\"Time\": \"2019-12-29T00:00:00\", \"Weekly Downloads\": 2524}, {\"Time\": \"2020-01-05T00:00:00\", \"Weekly Downloads\": 1402}, {\"Time\": \"2020-01-12T00:00:00\", \"Weekly Downloads\": 3351}, {\"Time\": \"2020-01-19T00:00:00\", \"Weekly Downloads\": 2521}, {\"Time\": \"2020-01-26T00:00:00\", \"Weekly Downloads\": 4035}, {\"Time\": \"2020-02-02T00:00:00\", \"Weekly Downloads\": 3006}, {\"Time\": \"2020-02-09T00:00:00\", \"Weekly Downloads\": 3056}, {\"Time\": \"2020-02-16T00:00:00\", \"Weekly Downloads\": 2546}, {\"Time\": \"2020-02-23T00:00:00\", \"Weekly Downloads\": 3016}, {\"Time\": \"2020-03-01T00:00:00\", \"Weekly Downloads\": 2694}, {\"Time\": \"2020-03-08T00:00:00\", \"Weekly Downloads\": 3051}, {\"Time\": \"2020-03-15T00:00:00\", \"Weekly Downloads\": 3281}, {\"Time\": \"2020-03-22T00:00:00\", \"Weekly Downloads\": 3663}, {\"Time\": \"2020-03-29T00:00:00\", \"Weekly Downloads\": 3724}, {\"Time\": \"2020-04-05T00:00:00\", \"Weekly Downloads\": 3635}, {\"Time\": \"2020-04-12T00:00:00\", \"Weekly Downloads\": 3130}, {\"Time\": \"2020-04-19T00:00:00\", \"Weekly Downloads\": 3788}, {\"Time\": \"2020-04-26T00:00:00\", \"Weekly Downloads\": 3431}, {\"Time\": \"2020-05-03T00:00:00\", \"Weekly Downloads\": 3129}, {\"Time\": \"2020-05-10T00:00:00\", \"Weekly Downloads\": 3538}, {\"Time\": \"2020-05-17T00:00:00\", \"Weekly Downloads\": 4136}, {\"Time\": \"2020-05-24T00:00:00\", \"Weekly Downloads\": 7752}, {\"Time\": \"2020-05-31T00:00:00\", \"Weekly Downloads\": 4194}, {\"Time\": \"2020-06-07T00:00:00\", \"Weekly Downloads\": 6276}, {\"Time\": \"2020-06-14T00:00:00\", \"Weekly Downloads\": 4288}, {\"Time\": \"2020-06-21T00:00:00\", \"Weekly Downloads\": 4166}, {\"Time\": \"2020-06-28T00:00:00\", \"Weekly Downloads\": 4885}, {\"Time\": \"2020-07-05T00:00:00\", \"Weekly Downloads\": 4270}, {\"Time\": \"2020-07-12T00:00:00\", \"Weekly Downloads\": 4395}, {\"Time\": \"2020-07-19T00:00:00\", \"Weekly Downloads\": 3965}, {\"Time\": \"2020-07-26T00:00:00\", \"Weekly Downloads\": 4139}, {\"Time\": \"2020-08-02T00:00:00\", \"Weekly Downloads\": 4892}, {\"Time\": \"2020-08-09T00:00:00\", \"Weekly Downloads\": 4347}, {\"Time\": \"2020-08-16T00:00:00\", \"Weekly Downloads\": 4454}, {\"Time\": \"2020-08-23T00:00:00\", \"Weekly Downloads\": 4661}, {\"Time\": \"2020-08-30T00:00:00\", \"Weekly Downloads\": 5280}, {\"Time\": \"2020-09-06T00:00:00\", \"Weekly Downloads\": 3906}, {\"Time\": \"2020-09-13T00:00:00\", \"Weekly Downloads\": 3929}, {\"Time\": \"2020-09-20T00:00:00\", \"Weekly Downloads\": 5093}, {\"Time\": \"2020-09-27T00:00:00\", \"Weekly Downloads\": 3900}, {\"Time\": \"2020-10-04T00:00:00\", \"Weekly Downloads\": 4894}, {\"Time\": \"2020-10-11T00:00:00\", \"Weekly Downloads\": 4340}, {\"Time\": \"2020-10-18T00:00:00\", \"Weekly Downloads\": 5790}, {\"Time\": \"2020-10-25T00:00:00\", \"Weekly Downloads\": 4712}, {\"Time\": \"2020-11-01T00:00:00\", \"Weekly Downloads\": 6135}, {\"Time\": \"2020-11-08T00:00:00\", \"Weekly Downloads\": 4421}, {\"Time\": \"2020-11-15T00:00:00\", \"Weekly Downloads\": 5448}, {\"Time\": \"2020-11-22T00:00:00\", \"Weekly Downloads\": 5747}, {\"Time\": \"2020-11-29T00:00:00\", \"Weekly Downloads\": 4008}, {\"Time\": \"2020-12-06T00:00:00\", \"Weekly Downloads\": 4825}, {\"Time\": \"2020-12-13T00:00:00\", \"Weekly Downloads\": 4979}, {\"Time\": \"2020-12-20T00:00:00\", \"Weekly Downloads\": 4107}, {\"Time\": \"2020-12-27T00:00:00\", \"Weekly Downloads\": 2969}, {\"Time\": \"2021-01-03T00:00:00\", \"Weekly Downloads\": 2432}, {\"Time\": \"2021-01-10T00:00:00\", \"Weekly Downloads\": 4745}, {\"Time\": \"2021-01-17T00:00:00\", \"Weekly Downloads\": 5765}, {\"Time\": \"2021-01-24T00:00:00\", \"Weekly Downloads\": 5727}, {\"Time\": \"2021-01-31T00:00:00\", \"Weekly Downloads\": 14105}, {\"Time\": \"2021-02-07T00:00:00\", \"Weekly Downloads\": 7858}, {\"Time\": \"2021-02-14T00:00:00\", \"Weekly Downloads\": 6973}, {\"Time\": \"2021-02-21T00:00:00\", \"Weekly Downloads\": 6123}, {\"Time\": \"2021-02-28T00:00:00\", \"Weekly Downloads\": 6657}, {\"Time\": \"2021-03-07T00:00:00\", \"Weekly Downloads\": 7453}, {\"Time\": \"2021-03-14T00:00:00\", \"Weekly Downloads\": 6807}, {\"Time\": \"2021-03-21T00:00:00\", \"Weekly Downloads\": 7588}, {\"Time\": \"2021-03-28T00:00:00\", \"Weekly Downloads\": 8090}, {\"Time\": \"2021-04-04T00:00:00\", \"Weekly Downloads\": 7931}, {\"Time\": \"2021-04-11T00:00:00\", \"Weekly Downloads\": 6876}, {\"Time\": \"2021-04-18T00:00:00\", \"Weekly Downloads\": 6705}, {\"Time\": \"2021-04-25T00:00:00\", \"Weekly Downloads\": 7438}, {\"Time\": \"2021-05-02T00:00:00\", \"Weekly Downloads\": 9161}, {\"Time\": \"2021-05-09T00:00:00\", \"Weekly Downloads\": 7250}, {\"Time\": \"2021-05-16T00:00:00\", \"Weekly Downloads\": 7594}, {\"Time\": \"2021-05-23T00:00:00\", \"Weekly Downloads\": 7539}, {\"Time\": \"2021-05-30T00:00:00\", \"Weekly Downloads\": 7214}, {\"Time\": \"2021-06-06T00:00:00\", \"Weekly Downloads\": 6572}, {\"Time\": \"2021-06-13T00:00:00\", \"Weekly Downloads\": 7454}, {\"Time\": \"2021-06-20T00:00:00\", \"Weekly Downloads\": 8697}, {\"Time\": \"2021-06-27T00:00:00\", \"Weekly Downloads\": 7070}, {\"Time\": \"2021-07-04T00:00:00\", \"Weekly Downloads\": 7461}, {\"Time\": \"2021-07-11T00:00:00\", \"Weekly Downloads\": 7142}, {\"Time\": \"2021-07-18T00:00:00\", \"Weekly Downloads\": 8363}, {\"Time\": \"2021-07-25T00:00:00\", \"Weekly Downloads\": 7682}, {\"Time\": \"2021-08-01T00:00:00\", \"Weekly Downloads\": 7688}, {\"Time\": \"2021-08-08T00:00:00\", \"Weekly Downloads\": 6992}, {\"Time\": \"2021-08-15T00:00:00\", \"Weekly Downloads\": 7268}, {\"Time\": \"2021-08-22T00:00:00\", \"Weekly Downloads\": 6722}, {\"Time\": \"2021-08-29T00:00:00\", \"Weekly Downloads\": 6862}, {\"Time\": \"2021-09-05T00:00:00\", \"Weekly Downloads\": 5997}, {\"Time\": \"2021-09-12T00:00:00\", \"Weekly Downloads\": 7013}, {\"Time\": \"2021-09-19T00:00:00\", \"Weekly Downloads\": 8976}, {\"Time\": \"2021-09-26T00:00:00\", \"Weekly Downloads\": 6991}, {\"Time\": \"2021-10-03T00:00:00\", \"Weekly Downloads\": 6245}, {\"Time\": \"2021-10-10T00:00:00\", \"Weekly Downloads\": 7453}, {\"Time\": \"2021-10-17T00:00:00\", \"Weekly Downloads\": 7205}, {\"Time\": \"2021-10-24T00:00:00\", \"Weekly Downloads\": 6772}, {\"Time\": \"2021-10-31T00:00:00\", \"Weekly Downloads\": 7287}, {\"Time\": \"2021-11-07T00:00:00\", \"Weekly Downloads\": 7344}, {\"Time\": \"2021-11-14T00:00:00\", \"Weekly Downloads\": 7520}, {\"Time\": \"2021-11-21T00:00:00\", \"Weekly Downloads\": 8799}, {\"Time\": \"2021-11-28T00:00:00\", \"Weekly Downloads\": 8041}, {\"Time\": \"2021-12-05T00:00:00\", \"Weekly Downloads\": 8575}, {\"Time\": \"2021-12-12T00:00:00\", \"Weekly Downloads\": 9563}, {\"Time\": \"2021-12-19T00:00:00\", \"Weekly Downloads\": 7752}, {\"Time\": \"2021-12-26T00:00:00\", \"Weekly Downloads\": 5814}, {\"Time\": \"2022-01-02T00:00:00\", \"Weekly Downloads\": 4513}, {\"Time\": \"2022-01-09T00:00:00\", \"Weekly Downloads\": 7157}, {\"Time\": \"2022-01-16T00:00:00\", \"Weekly Downloads\": 8366}, {\"Time\": \"2022-01-23T00:00:00\", \"Weekly Downloads\": 9424}, {\"Time\": \"2022-01-30T00:00:00\", \"Weekly Downloads\": 7553}, {\"Time\": \"2022-02-06T00:00:00\", \"Weekly Downloads\": 10263}, {\"Time\": \"2022-02-13T00:00:00\", \"Weekly Downloads\": 10756}, {\"Time\": \"2022-02-20T00:00:00\", \"Weekly Downloads\": 9998}, {\"Time\": \"2022-02-27T00:00:00\", \"Weekly Downloads\": 10215}, {\"Time\": \"2022-03-06T00:00:00\", \"Weekly Downloads\": 13896}, {\"Time\": \"2022-03-13T00:00:00\", \"Weekly Downloads\": 12162}, {\"Time\": \"2022-03-20T00:00:00\", \"Weekly Downloads\": 11788}, {\"Time\": \"2022-03-27T00:00:00\", \"Weekly Downloads\": 10712}, {\"Time\": \"2022-04-03T00:00:00\", \"Weekly Downloads\": 10896}, {\"Time\": \"2022-04-10T00:00:00\", \"Weekly Downloads\": 12203}, {\"Time\": \"2022-04-17T00:00:00\", \"Weekly Downloads\": 9111}, {\"Time\": \"2022-04-24T00:00:00\", \"Weekly Downloads\": 9887}, {\"Time\": \"2022-05-01T00:00:00\", \"Weekly Downloads\": 10031}, {\"Time\": \"2022-05-08T00:00:00\", \"Weekly Downloads\": 10408}, {\"Time\": \"2022-05-15T00:00:00\", \"Weekly Downloads\": 9631}, {\"Time\": \"2022-05-22T00:00:00\", \"Weekly Downloads\": 10551}, {\"Time\": \"2022-05-29T00:00:00\", \"Weekly Downloads\": 10324}, {\"Time\": \"2022-06-05T00:00:00\", \"Weekly Downloads\": 10424}, {\"Time\": \"2022-06-12T00:00:00\", \"Weekly Downloads\": 10059}, {\"Time\": \"2022-06-19T00:00:00\", \"Weekly Downloads\": 11124}, {\"Time\": \"2022-06-26T00:00:00\", \"Weekly Downloads\": 9802}, {\"Time\": \"2022-07-03T00:00:00\", \"Weekly Downloads\": 10573}, {\"Time\": \"2022-07-10T00:00:00\", \"Weekly Downloads\": 9636}, {\"Time\": \"2022-07-17T00:00:00\", \"Weekly Downloads\": 9666}, {\"Time\": \"2022-07-24T00:00:00\", \"Weekly Downloads\": 9221}, {\"Time\": \"2022-07-31T00:00:00\", \"Weekly Downloads\": 9170}, {\"Time\": \"2022-08-07T00:00:00\", \"Weekly Downloads\": 9987}, {\"Time\": \"2022-08-14T00:00:00\", \"Weekly Downloads\": 11584}, {\"Time\": \"2022-08-21T00:00:00\", \"Weekly Downloads\": 8821}, {\"Time\": \"2022-08-28T00:00:00\", \"Weekly Downloads\": 11153}, {\"Time\": \"2022-09-04T00:00:00\", \"Weekly Downloads\": 10651}, {\"Time\": \"2022-09-11T00:00:00\", \"Weekly Downloads\": 10265}, {\"Time\": \"2022-09-18T00:00:00\", \"Weekly Downloads\": 15179}, {\"Time\": \"2022-09-25T00:00:00\", \"Weekly Downloads\": 11884}, {\"Time\": \"2022-10-02T00:00:00\", \"Weekly Downloads\": 12366}, {\"Time\": \"2022-10-09T00:00:00\", \"Weekly Downloads\": 13484}, {\"Time\": \"2022-10-16T00:00:00\", \"Weekly Downloads\": 12373}, {\"Time\": \"2022-10-23T00:00:00\", \"Weekly Downloads\": 11822}, {\"Time\": \"2022-10-30T00:00:00\", \"Weekly Downloads\": 10830}, {\"Time\": \"2022-11-06T00:00:00\", \"Weekly Downloads\": 12358}, {\"Time\": \"2022-11-13T00:00:00\", \"Weekly Downloads\": 13362}, {\"Time\": \"2022-11-20T00:00:00\", \"Weekly Downloads\": 16985}, {\"Time\": \"2022-11-27T00:00:00\", \"Weekly Downloads\": 12308}, {\"Time\": \"2022-12-04T00:00:00\", \"Weekly Downloads\": 13362}, {\"Time\": \"2022-12-11T00:00:00\", \"Weekly Downloads\": 12713}, {\"Time\": \"2022-12-18T00:00:00\", \"Weekly Downloads\": 13958}, {\"Time\": \"2022-12-25T00:00:00\", \"Weekly Downloads\": 11078}, {\"Time\": \"2023-01-01T00:00:00\", \"Weekly Downloads\": 5871}, {\"Time\": \"2023-01-08T00:00:00\", \"Weekly Downloads\": 11883}, {\"Time\": \"2023-01-15T00:00:00\", \"Weekly Downloads\": 18682}, {\"Time\": \"2023-01-22T00:00:00\", \"Weekly Downloads\": 16855}, {\"Time\": \"2023-01-29T00:00:00\", \"Weekly Downloads\": 15867}, {\"Time\": \"2023-02-05T00:00:00\", \"Weekly Downloads\": 16765}, {\"Time\": \"2023-02-12T00:00:00\", \"Weekly Downloads\": 16318}, {\"Time\": \"2023-02-19T00:00:00\", \"Weekly Downloads\": 18957}, {\"Time\": \"2023-02-26T00:00:00\", \"Weekly Downloads\": 18156}, {\"Time\": \"2023-03-05T00:00:00\", \"Weekly Downloads\": 14680}, {\"Time\": \"2023-03-12T00:00:00\", \"Weekly Downloads\": 18623}, {\"Time\": \"2023-03-19T00:00:00\", \"Weekly Downloads\": 17443}, {\"Time\": \"2023-03-26T00:00:00\", \"Weekly Downloads\": 17067}, {\"Time\": \"2023-04-02T00:00:00\", \"Weekly Downloads\": 14985}, {\"Time\": \"2023-04-09T00:00:00\", \"Weekly Downloads\": 16479}, {\"Time\": \"2023-04-16T00:00:00\", \"Weekly Downloads\": 18721}, {\"Time\": \"2023-04-23T00:00:00\", \"Weekly Downloads\": 19186}, {\"Time\": \"2023-04-30T00:00:00\", \"Weekly Downloads\": 18173}, {\"Time\": \"2023-05-07T00:00:00\", \"Weekly Downloads\": 15336}, {\"Time\": \"2023-05-14T00:00:00\", \"Weekly Downloads\": 18879}, {\"Time\": \"2023-05-21T00:00:00\", \"Weekly Downloads\": 16927}, {\"Time\": \"2023-05-28T00:00:00\", \"Weekly Downloads\": 18583}, {\"Time\": \"2023-06-04T00:00:00\", \"Weekly Downloads\": 16137}, {\"Time\": \"2023-06-11T00:00:00\", \"Weekly Downloads\": 18142}, {\"Time\": \"2023-06-18T00:00:00\", \"Weekly Downloads\": 21023}, {\"Time\": \"2023-06-25T00:00:00\", \"Weekly Downloads\": 16973}, {\"Time\": \"2023-07-02T00:00:00\", \"Weekly Downloads\": 16132}, {\"Time\": \"2023-07-09T00:00:00\", \"Weekly Downloads\": 17256}, {\"Time\": \"2023-07-16T00:00:00\", \"Weekly Downloads\": 19053}, {\"Time\": \"2023-07-23T00:00:00\", \"Weekly Downloads\": 21099}, {\"Time\": \"2023-07-30T00:00:00\", \"Weekly Downloads\": 28820}, {\"Time\": \"2023-08-06T00:00:00\", \"Weekly Downloads\": 27863}, {\"Time\": \"2023-08-13T00:00:00\", \"Weekly Downloads\": 26169}, {\"Time\": \"2023-08-20T00:00:00\", \"Weekly Downloads\": 24733}, {\"Time\": \"2023-08-27T00:00:00\", \"Weekly Downloads\": 27217}, {\"Time\": \"2023-09-03T00:00:00\", \"Weekly Downloads\": 22154}, {\"Time\": \"2023-09-10T00:00:00\", \"Weekly Downloads\": 24957}, {\"Time\": \"2023-09-17T00:00:00\", \"Weekly Downloads\": 23944}]}}, {\"mode\": \"vega-lite\"});\n",
"</script>"
],
"text/plain": [
"alt.Chart(...)"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(\n",
" alt.Chart(\n",
" (\n",
" anndata_df_filtered\n",
" .groupby(pd.Grouper(freq=\"W\"))\n",
" [[\"num_downloads\"]].sum()\n",
" .iloc[:-1]\n",
" .reset_index()\n",
" .rename(columns={\"num_downloads\": \"Weekly Downloads\", \"day\": \"Time\"})\n",
" )\n",
" )\n",
" .mark_line()\n",
" .encode(x=\"Time\", y=\"Weekly Downloads\")\n",
" .properties(width=300, height=150)\n",
")\n",
" "
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.18"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
@flying-sheep
Copy link

two alternative data sources (example with scanpy as package)

both have APIs, and I think neither wants money for casual use

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