diff --git a/notebooks/case1_bike_count.ipynb b/notebooks/case1_bike_count.ipynb index 1d09350..03be750 100644 --- a/notebooks/case1_bike_count.ipynb +++ b/notebooks/case1_bike_count.ipynb @@ -104,6 +104,9 @@ "execution_count": 3, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -199,6 +202,9 @@ "execution_count": 4, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -294,6 +300,9 @@ "execution_count": 5, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -319,6 +328,9 @@ "execution_count": 6, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -388,6 +400,9 @@ "execution_count": 7, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -458,7 +473,10 @@ "cell_type": "code", "execution_count": 11, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [ { @@ -545,7 +563,10 @@ "cell_type": "code", "execution_count": 12, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [ { @@ -560,7 +581,7 @@ }, { "data": { - "image/png": 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\n", + "image/png": 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" ] @@ -605,14 +626,17 @@ "cell_type": "code", "execution_count": 14, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "11.8 s ± 0 ns per loop (mean ± std. dev. of 1 run, 1 loop each)\n" + "17.1 s ± 0 ns per loop (mean ± std. dev. of 1 run, 1 loop each)\n" ] } ], @@ -631,14 +655,17 @@ "cell_type": "code", "execution_count": 15, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "468 ms ± 29.6 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" + "551 ms ± 22.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] } ], @@ -722,7 +749,10 @@ "cell_type": "code", "execution_count": 17, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [ { @@ -878,7 +908,10 @@ "cell_type": "code", "execution_count": 20, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [ { @@ -904,7 +937,7 @@ } ], "source": [ - "pd.Series(df.index).diff()" + "df.index.to_series().diff()" ] }, { @@ -918,7 +951,10 @@ "cell_type": "code", "execution_count": 21, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [ { @@ -962,7 +998,7 @@ } ], "source": [ - "pd.Series(df.index).diff().value_counts()" + "df.index.to_series().diff().value_counts()" ] }, { @@ -978,7 +1014,10 @@ "cell_type": "code", "execution_count": 22, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [ { @@ -1101,6 +1140,9 @@ "execution_count": 23, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -1186,6 +1228,9 @@ "execution_count": 25, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -1318,7 +1363,7 @@ "\n", "**EXERCISE**\n", "\n", - "What is the average number of bikers passing each 15 min?\n", + "What is the average number of bikers passing every 15 min in each direction?\n", "\n", "
Hints\n", "\n", @@ -1332,6 +1377,9 @@ "execution_count": 26, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -1377,6 +1425,9 @@ "execution_count": 27, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -1421,6 +1472,9 @@ "execution_count": 28, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -1503,6 +1557,9 @@ "execution_count": 31, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -1594,6 +1651,9 @@ "execution_count": 33, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -1660,6 +1720,9 @@ "execution_count": 35, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -1743,6 +1806,9 @@ "execution_count": 36, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -1826,6 +1892,9 @@ "execution_count": 38, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -1861,6 +1930,9 @@ "execution_count": 39, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -1903,6 +1975,9 @@ "execution_count": 40, "metadata": { "collapsed": false, + "jupyter": { + "outputs_hidden": false + }, "tags": [ "nbtutor-solution" ] @@ -1976,7 +2051,10 @@ "cell_type": "code", "execution_count": 44, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [ { @@ -2011,11 +2089,23 @@ "**Daily pattern:**" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df_hourly = df.resample('H').sum()" + ] + }, { "cell_type": "code", "execution_count": 79, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [ { @@ -2079,7 +2169,10 @@ "cell_type": "code", "execution_count": 65, "metadata": { - "collapsed": false + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } }, "outputs": [ { @@ -2136,7 +2229,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.12" + "version": "3.10.2" }, "nav_menu": {}, "toc": { diff --git a/notebooks/case1_bike_count.md b/notebooks/case1_bike_count.md index 9381840..63d363a 100644 --- a/notebooks/case1_bike_count.md +++ b/notebooks/case1_bike_count.md @@ -5,7 +5,7 @@ jupytext: extension: .md format_name: myst format_version: 0.13 - jupytext_version: 1.13.3 + jupytext_version: 1.13.6 kernelspec: display_name: Python 3 (ipykernel) language: python @@ -283,13 +283,13 @@ df = pd.read_csv("bike_count_interim.csv", index_col=0, parse_dates=True) The number of bikers are counted for intervals of approximately 15 minutes. But let's check if this is indeed the case. Calculate the difference between each of the consecutive values of the index. We can use the `Series.diff()` method: ```{code-cell} ipython3 -pd.Series(df.index).diff() +df.index.to_series().diff() ``` The count of the possible intervals is of interest: ```{code-cell} ipython3 -pd.Series(df.index).diff().value_counts() +df.index.to_series().diff().value_counts() ``` There are a few records that are not exactly 15min. But given it are only a few ones, we will ignore this for the current case study and just keep them for this explorative study. @@ -368,7 +368,7 @@ df[(df['direction_centre'] < 3) | (df['direction_mariakerke'] < 3)] **EXERCISE** -What is the average number of bikers passing each 15 min? +What is the average number of bikers passing every 15 min in each direction?
Hints @@ -593,6 +593,10 @@ df_daily.groupby(df_daily.index.dayofweek).mean().plot(kind='bar') **Daily pattern:** +```{code-cell} ipython3 +df_hourly = df.resample('H').sum() +``` + ```{code-cell} ipython3 df_hourly.groupby(df_hourly.index.hour).mean().plot() ```