Spaces:
Build error
Build error
File size: 2,834 Bytes
8744085 e48d543 8744085 02c2d7e 8744085 df4398a 8744085 b748dad 8744085 b748dad 8744085 e2db848 02c2d7e e2db848 02c2d7e e2db848 02c2d7e e2db848 8744085 e48d543 e2db848 8744085 e2db848 8744085 e48d543 8744085 e48d543 8744085 e48d543 8744085 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 |
import base64
import altair as alt
import pandas as pd
import streamlit as st
from PIL import Image
from .configs import SupportedFiles
@st.cache
def get_logo(path):
return Image.open(path)
@st.experimental_memo
def read_file(uploaded_file) -> pd.DataFrame:
file_type = uploaded_file.name.split(".")[-1]
read_fn = SupportedFiles[file_type].value[0]
df = read_fn(uploaded_file)
df = df.dropna()
return df
@st.cache
def convert_df(df):
# IMPORTANT: Cache the conversion to prevent computation on every rerun
return df.to_csv(index=False, sep=";").encode("utf-8")
def download_button(dataframe: pd.DataFrame, name: str):
csv = dataframe.to_csv(index=False)
# some strings <-> bytes conversions necessary here
b64 = base64.b64encode(csv.encode()).decode()
href = f'<a href="data:file/csv;base64,{b64}" download="{name}.csv">Download</a>'
st.write(href, unsafe_allow_html=True)
def plot_labels_prop(data: pd.DataFrame, label_column: str):
unique_value_limit = 100
if data[label_column].nunique() > unique_value_limit:
st.warning(
f"""
The column you selected has more than {unique_value_limit}.
Are you sure it's the right column? If it is, please note that
this will impact __Wordify__ performance.
"""
)
return
source = (
data[label_column]
.value_counts()
.reset_index()
.rename(columns={"index": "Labels", label_column: "Counts"})
)
source["Props"] = source["Counts"] / source["Counts"].sum()
source["Proportions"] = (source["Props"].round(3) * 100).map("{:,.2f}".format) + "%"
bars = (
alt.Chart(source)
.mark_bar()
.encode(
x=alt.X("Labels:O", sort="-y"),
y="Counts:Q",
)
)
text = bars.mark_text(align="center", baseline="middle", dy=15).encode(
text="Proportions:O"
)
return (bars + text).properties(height=300)
def plot_nchars(data: pd.DataFrame, text_column: str):
source = data[text_column].str.len().to_frame()
plot = (
alt.Chart(source)
.mark_bar()
.encode(
alt.X(
f"{text_column}:Q", bin=True, axis=alt.Axis(title="# chars per text")
),
alt.Y("count()", axis=alt.Axis(title="")),
)
)
return plot.properties(height=300)
def plot_score(data: pd.DataFrame, label_col: str, label: str):
source = (
data.loc[data[label_col] == label]
.sort_values("score", ascending=False)
.head(100)
)
plot = (
alt.Chart(source)
.mark_bar()
.encode(
y=alt.Y("word:O", sort="-x"),
x="score:Q",
)
)
return plot.properties(height=max(30 * source.shape[0], 50))
|