Pandas notes
Contents |
Using Python Pandas package for data analysis. Leo's notes.
Data manipulation
Import data from a CSV file to a dataframe
df = pd.read_csv("filename.csv")
Filter the data by a field value
df2 = df.loc[df['Tagid'] == "1234"]
Get all unique values (for example, for the Tagid field)
allTags = df.Tagid.unique()
Pivot the table, where the values become columns. For example, to create a plot that uses unique values (of Tagid) as the series.
dfTags = df.pivot(columns='Tagid', values='RSSI')
Plot options
Define the colors of the plot data
df.plot(color="rgbk")
Different plot types (markers)
df.plot(marker='.')
Limit the X axis values:
df.plot(xlim=(0,4000))
Naming the axis
ax = df.plot() ax.set_ylabel(AntNames[x])
Placement of the legend (Below-left of the plot)
df.plot().legend(loc='upper left', bbox_to_anchor=(0, 0))
Removing the legend
ax = df.plot() ax.legend_.remove()
Plotting means and std: link
mymean = byTagAnt.RSSI.mean() mystd = byTagAnt.RSSI.std() mymean.plot(kind="bar", yerr=mystd);
Plotting with various parameters:
p = mymean.plot(figsize=(15,5),legend=False,kind="bar",rot=45,color="green",fontsize=16,yerr=mystd);